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D04178DDE54F21A248DAFF3F1582EB4BF1E9AC43 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/_nodes_TA.html?context=cdpaas&locale=en | Text Analytics (SPSS Modeler) | Text Analytics
SPSS Modeler offers nodes that are specialized for handling text.
The Text Analytics nodes offer powerful text analytics capabilities, using advanced linguistic technologies and Natural Language Processing (NLP) to rapidly process a large variety of unstructured text data and, from this text, extract... | # Text Analytics #
SPSS Modeler offers nodes that are specialized for handling text\.
The Text Analytics nodes offer powerful text analytics capabilities, using advanced linguistic technologies and Natural Language Processing (NLP) to rapidly process a large variety of unstructured text data and, from this text, extr... | <!doctype html>
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<meta name="description" content="SPSS Modeler offers nodes that are specialized for handling text.">
<met... |
42E228E8218A4FDEF9F2CA0DB53B5B594A475B88 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/_nodes_TA_intro.html?context=cdpaas&locale=en | About text mining (SPSS Modeler) | About text mining
Today, an increasing amount of information is being held in unstructured and semi-structured formats, such as customer e-mails, call center notes, open-ended survey responses, news feeds, web forms, etc. This abundance of information poses a problem to many organizations that ask themselves: How ca... | # About text mining #
Today, an increasing amount of information is being held in unstructured and semi\-structured formats, such as customer e\-mails, call center notes, open\-ended survey responses, news feeds, web forms, etc\. This abundance of information poses a problem to many organizations that ask themselves: ... | <!doctype html>
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<meta name="description" content="Today, an increasing amount of information is being held in unstructure... |
3602C22051EA1148B07446605DD3C57BF7830C3A | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/_nodes_TA_intro_categorize.html?context=cdpaas&locale=en | How categorization works (SPSS Modeler) | How categorization works
When creating category models in Text Analytics, there are several different techniques you can choose from to create categories. Because every dataset is unique, the number of techniques and the order in which you apply them may change.
Since your interpretation of the results may be diffe... | # How categorization works #
When creating category models in Text Analytics, there are several different techniques you can choose from to create categories\. Because every dataset is unique, the number of techniques and the order in which you apply them may change\.
Since your interpretation of the results may be d... | <!doctype html>
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<meta name="description" content="When creating category models in Text Analytics, there are several diff... |
F976E639BDE8A2B880E46D94F4C832B6ED9A9303 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/_nodes_TA_intro_extract.html?context=cdpaas&locale=en | How extraction works (SPSS Modeler) | How extraction works
During the extraction of key concepts and ideas from your responses, Text Analytics relies on linguistics-based text analysis. This approach offers the speed and cost effectiveness of statistics-based systems. But it offers a far higher degree of accuracy, while requiring far less human interven... | # How extraction works #
During the extraction of key concepts and ideas from your responses, Text Analytics relies on linguistics\-based text analysis\. This approach offers the speed and cost effectiveness of statistics\-based systems\. But it offers a far higher degree of accuracy, while requiring far less human in... | <!doctype html>
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<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
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<meta name="description" content="During the extraction of key concepts and ideas from your responses, Te... |
B0B80EB59E769546EEDF8CA32A493BF38C6A9707 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/_nodes_export.html?context=cdpaas&locale=en | Export nodes (SPSS Modeler) | Export
Export nodes provide a mechanism for exporting data in various formats to interface with your other software tools.
| # Export #
Export nodes provide a mechanism for exporting data in various formats to interface with your other software tools\.
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B6DC074F83F9E8984B9CD3A3BF5B392BC4A61844 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/_nodes_extension.html?context=cdpaas&locale=en | Extension nodes (SPSS Modeler) | Extension nodes
SPSS Modeler supports the languages R and Apache Spark (via Python).
To complement SPSS Modeler and its data mining abilities, several Extension nodes are available to enable expert users to input their own R scripts or Python for Spark scripts to carry out data processing, model building, and mode... | # Extension nodes #
SPSS Modeler supports the languages R and Apache Spark (via Python)\.
To complement SPSS Modeler and its data mining abilities, several Extension nodes are available to enable expert users to input their own R scripts or Python for Spark scripts to carry out data processing, model building, and m... | <!doctype html>
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<meta name="description" content="SPSS Modeler supports the languages R and Apache Spark (via Python).">
... |
4E571695FB4E12489157704D87F89DF5DAD1A580 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/_nodes_field_operations.html?context=cdpaas&locale=en | Field Operations nodes (SPSS Modeler) | Field Operations
After an initial data exploration, you will probably need to select, clean, or construct data in preparation for analysis. The Field Operations palette contains many nodes useful for this transformation and preparation.
For example, using a Derive node, you might create an attribute that is not cur... | # Field Operations #
After an initial data exploration, you will probably need to select, clean, or construct data in preparation for analysis\. The Field Operations palette contains many nodes useful for this transformation and preparation\.
For example, using a Derive node, you might create an attribute that is not... | <!doctype html>
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<meta name="description" content="After an initial data exploration, you will probably need to select, cl... |
2AEC614E6CBE5D4963D53DEC7E22877D5A1BEDE8 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/_nodes_graphs.html?context=cdpaas&locale=en | Graph nodes (SPSS Modeler) | Graphs
Several phases of the data mining process use graphs and charts to explore data brought in to watsonx.ai.
For example, you can connect a Plot or Distribution node to a data source to gain insight into data types and distributions. You can then perform record and field manipulations to prepare the data for d... | # Graphs #
Several phases of the data mining process use graphs and charts to explore data brought in to watsonx\.ai\.
For example, you can connect a Plot or Distribution node to a data source to gain insight into data types and distributions\. You can then perform record and field manipulations to prepare the data ... | <!doctype html>
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="Several phases of the data mining process use graphs and charts to expl... |
A9FA1D31F4CC6018DAF5B927908210846B082675 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/_nodes_import.html?context=cdpaas&locale=en | Import nodes (SPSS Modeler) | Import
Use Import nodes to import data stored in various formats, or to generate your own synthetic data.
| # Import #
Use Import nodes to import data stored in various formats, or to generate your own synthetic data\.
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<meta name="description" content="Use Import nodes to import data stored in various formats, or to genera... |
7E30541B3A12F403ADCB02F90BC96134CE6B6386 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/_nodes_modeling.html?context=cdpaas&locale=en | Modeling nodes (SPSS Modeler) | Modeling
Watsonx.ai offers a variety of modeling methods taken from machine learning, artificial intelligence, and statistics.
The methods available on the palette allow you to derive new information from your data and to develop predictive models. Each method has certain strengths and is best suited for particular... | # Modeling #
Watsonx\.ai offers a variety of modeling methods taken from machine learning, artificial intelligence, and statistics\.
The methods available on the palette allow you to derive new information from your data and to develop predictive models\. Each method has certain strengths and is best suited for parti... | <!doctype html>
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="Watsonx.ai offers a variety of modeling methods taken from machine lear... |
A56C821C7EE483D01E4338397F62DDD6CB6D5E9F | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/_nodes_outputs.html?context=cdpaas&locale=en | Output nodes (SPSS Modeler) | Outputs
Output nodes provide the means to obtain information about your data and models. They also provide a mechanism for exporting data in various formats to interface with your other software tools.
| # Outputs #
Output nodes provide the means to obtain information about your data and models\. They also provide a mechanism for exporting data in various formats to interface with your other software tools\.
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<meta name="description" content="Output nodes provide the means to obtain information about your data an... |
09BB38FB6DF4C562A478D6D3DC54D22823F922FB | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/_nodes_record_operations.html?context=cdpaas&locale=en | Record Operations nodes (SPSS Modeler) | Record Operations
Record Operations nodes are useful for making changes to data at the record level. These operations are important during the data understanding and data preparation phases of data mining because they allow you to tailor the data to your particular business need.
For example, based on the results o... | # Record Operations #
Record Operations nodes are useful for making changes to data at the record level\. These operations are important during the data understanding and data preparation phases of data mining because they allow you to tailor the data to your particular business need\.
For example, based on the resul... | <!doctype html>
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<meta name="description" content="Record Operations nodes are useful for making changes to data at the re... |
8435D88B7DC8317B982E1EAA57FA55B8391D00CF | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/aggregate.html?context=cdpaas&locale=en | Aggregate node (SPSS Modeler) | Aggregate node
Aggregation is a data preparation task frequently used to reduce the size of a dataset. Before proceeding with aggregation, you should take time to clean the data, concentrating especially on missing values. A aggregation, potentially useful information regarding missing values may be lost.
You can u... | # Aggregate node #
Aggregation is a data preparation task frequently used to reduce the size of a dataset\. Before proceeding with aggregation, you should take time to clean the data, concentrating especially on missing values\. A aggregation, potentially useful information regarding missing values may be lost\.
You ... | <!doctype html>
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<meta name="description" content="Aggregation is a data preparation task frequently used to reduce the si... |
6D7B948346F167B5390A0E56E1B6DE83AE31A19A | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/analysis.html?context=cdpaas&locale=en | Analysis node (SPSS Modeler) | Analysis node
With the Analysis node, you can evaluate the ability of a model to generate accurate predictions. Analysis nodes perform various comparisons between predicted values and actual values (your target field) for one or more model nuggets. You can also use Analysis nodes to compare predictive models to othe... | # Analysis node #
With the Analysis node, you can evaluate the ability of a model to generate accurate predictions\. Analysis nodes perform various comparisons between predicted values and actual values (your target field) for one or more model nuggets\. You can also use Analysis nodes to compare predictive models to ... | <!doctype html>
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<meta name="description" content="With the Analysis node, you can evaluate the ability of a model to gene... |
35A87CAEDB1F1B6739159B9C7A31CCE7C8978431 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/anomalydetection.html?context=cdpaas&locale=en | Anomaly node (SPSS Modeler) | Anomaly node
Anomaly detection models are used to identify outliers, or unusual cases, in the data. Unlike other modeling methods that store rules about unusual cases, anomaly detection models store information on what normal behavior looks like. This makes it possible to identify outliers even if they do not confor... | # Anomaly node #
Anomaly detection models are used to identify outliers, or unusual cases, in the data\. Unlike other modeling methods that store rules about unusual cases, anomaly detection models store information on what normal behavior looks like\. This makes it possible to identify outliers even if they do not co... | <!doctype html>
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<meta name="description" content="Anomaly detection models are used to identify outliers, or unusual case... |
F05134C8C952A7585B82A042B14BCF1234AF9329 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/anonymize.html?context=cdpaas&locale=en | Anonymize node (SPSS Modeler) | Anonymize node
With the Anonymize node, you can disguise field names, field values, or both when working with data that's to be included in a model downstream of the node. In this way, the generated model can be freely distributed (for example, to Technical Support) with no danger that unauthorized users will be abl... | # Anonymize node #
With the Anonymize node, you can disguise field names, field values, or both when working with data that's to be included in a model downstream of the node\. In this way, the generated model can be freely distributed (for example, to Technical Support) with no danger that unauthorized users will be ... | <!doctype html>
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<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="With the Anonymize node, you can disguise field names, field values, or... |
4C83F9C21CA1E70077C8004BD26FE5FB0FC947EB | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/append.html?context=cdpaas&locale=en | Append node (SPSS Modeler) | Append node
You can use Append nodes to concatenate sets of records. Unlike Merge nodes, which join records from different sources together, Append nodes read and pass downstream all of the records from one source until there are no more. Then the records from the next source are read using the same data structure (... | # Append node #
You can use Append nodes to concatenate sets of records\. Unlike Merge nodes, which join records from different sources together, Append nodes read and pass downstream all of the records from one source until there are no more\. Then the records from the next source are read using the same data structu... | <!doctype html>
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="You can use Append nodes to concatenate sets of records. Unlike Merge n... |
E14741F9A90592B67437AAED4B7042CD3DC268A8 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/applyextension.html?context=cdpaas&locale=en | Extension model nugget (SPSS Modeler) | Extension model nugget
The Extension model nugget is generated and placed on your flow canvas after running the Extension Model node, which contains your R script or Python for Spark script that defines the model building and model scoring.
By default, the Extension model nugget contains the script that's used for ... | # Extension model nugget #
The Extension model nugget is generated and placed on your flow canvas after running the Extension Model node, which contains your R script or Python for Spark script that defines the model building and model scoring\.
By default, the Extension model nugget contains the script that's used f... | <!doctype html>
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<meta name="description" content="The Extension model nugget is generated and placed on your flow canvas ... |
9346A72CFCD74DFDA05213A2A321BF9CFB823358 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/apriori.html?context=cdpaas&locale=en | Apriori node (SPSS Modeler) | Apriori node
The Apriori node discovers association rules in your data.
Association rules are statements of the form:
if antecedent(s) then consequent(s)
For example, if a customer purchases a razor and after shave, then that customer will purchase shaving cream with 80% confidence. Apriori extracts a set of r... | # Apriori node #
The Apriori node discovers association rules in your data\.
Association rules are statements of the form:
if antecedent(s) then consequent(s)
For example, if a customer purchases a razor and after shave, then that customer will purchase shaving cream with 80% confidence\. Apriori extracts a ... | <!doctype html>
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<meta name="description" content="The Apriori node discovers association rules in your data.">
<meta na... |
27091A60BA512E180C699261ECFFDC3A621418A5 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/associationrules.html?context=cdpaas&locale=en | Association Rules node (SPSS Modeler) | Association Rules node
Association rules associate a particular conclusion (the purchase of a particular product, for example) with a set of conditions (the purchase of several other products, for example).
For example, the rule
beer <= cannedveg & frozenmeal (173, 17.0%, 0.84)
states that beer often occurs when ... | # Association Rules node #
Association rules associate a particular conclusion (the purchase of a particular product, for example) with a set of conditions (the purchase of several other products, for example)\.
For example, the rule
beer <= cannedveg & frozenmeal (173, 17.0%, 0.84)
states that `beer` often occ... | <!doctype html>
<html lang="en-us">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="Association rules associate a particular conclusion (the purchase of a ... |
1ACF5ED461253F09DB844C2D84C1AE21277BC1E6 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/autoclassifier.html?context=cdpaas&locale=en | Auto Classifier node (SPSS Modeler) | Auto Classifier node
The Auto Classifier node estimates and compares models for either nominal (set) or binary (yes/no) targets, using a number of different methods, enabling you to try out a variety of approaches in a single modeling run. You can select the algorithms to use, and experiment with multiple combinatio... | # Auto Classifier node #
The Auto Classifier node estimates and compares models for either nominal (set) or binary (yes/no) targets, using a number of different methods, enabling you to try out a variety of approaches in a single modeling run\. You can select the algorithms to use, and experiment with multiple combina... | <!doctype html>
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="The Auto Classifier node estimates and compares models for either nomin... |
3A9DC582441C2474E183DA0E7DAC20FB182842C2 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/autocluster.html?context=cdpaas&locale=en | Auto Cluster node (SPSS Modeler) | Auto Cluster node
The Auto Cluster node estimates and compares clustering models that identify groups of records with similar characteristics. The node works in the same manner as other automated modeling nodes, enabling you to experiment with multiple combinations of options in a single modeling pass. Models can be... | # Auto Cluster node #
The Auto Cluster node estimates and compares clustering models that identify groups of records with similar characteristics\. The node works in the same manner as other automated modeling nodes, enabling you to experiment with multiple combinations of options in a single modeling pass\. Models ca... | <!doctype html>
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="The Auto Cluster node estimates and compares clustering models that ide... |
FD94481E337829121072F5E46CC39B6290E43B44 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/autodataprep.html?context=cdpaas&locale=en | Auto Data Prep node (SPSS Modeler) | Auto Data Prep node
Preparing data for analysis is one of the most important steps in any project—and traditionally, one of the most time consuming. Automated Data Preparation (ADP) handles the task for you, analyzing your data and identifying fixes, screening out fields that are problematic or not likely to be usef... | # Auto Data Prep node #
Preparing data for analysis is one of the most important steps in any project—and traditionally, one of the most time consuming\. Automated Data Preparation (ADP) handles the task for you, analyzing your data and identifying fixes, screening out fields that are problematic or not likely to be u... | <!doctype html>
<html lang="en-us">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="Preparing data for analysis is one of the most important steps in any p... |
9D9C67189BE5D6DB22575CF01A75BD5826B92074 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/autonumeric.html?context=cdpaas&locale=en | Auto Numeric node (SPSS Modeler) | Auto Numeric node
The Auto Numeric node estimates and compares models for continuous numeric range outcomes using a number of different methods, enabling you to try out a variety of approaches in a single modeling run. You can select the algorithms to use, and experiment with multiple combinations of options. For ex... | # Auto Numeric node #
The Auto Numeric node estimates and compares models for continuous numeric range outcomes using a number of different methods, enabling you to try out a variety of approaches in a single modeling run\. You can select the algorithms to use, and experiment with multiple combinations of options\. Fo... | <!doctype html>
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<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="The Auto Numeric node estimates and compares models for continuous nume... |
0294AB8C0FBC393F5C227A0F8BEBCCDC67B78B1D | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/balance.html?context=cdpaas&locale=en | Balance node (SPSS Modeler) | Balance node
You can use Balance nodes to correct imbalances in datasets so they conform to specified test criteria.
For example, suppose that a dataset has only two values--low or high--and that 90% of the cases are low while only 10% of the cases are high. Many modeling techniques have trouble with such biased da... | # Balance node #
You can use Balance nodes to correct imbalances in datasets so they conform to specified test criteria\.
For example, suppose that a dataset has only two values\-\-`low` or `high`\-\-and that 90% of the cases are `low` while only 10% of the cases are `high`\. Many modeling techniques have trouble wit... | <!doctype html>
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="You can use Balance nodes to correct imbalances in datasets so they con... |
1D5D80DFF65EE4195713EEEB43F1291B79779A6B | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/bayesnet.html?context=cdpaas&locale=en | Bayes Net node (SPSS Modeler) | Bayes Net node
The Bayesian Network node enables you to build a probability model by combining observed and recorded evidence with "common-sense" real-world knowledge to establish the likelihood of occurrences by using seemingly unlinked attributes. The node focuses on Tree Augmented Naïve Bayes (TAN) and Markov Bla... | # Bayes Net node #
The Bayesian Network node enables you to build a probability model by combining observed and recorded evidence with "common\-sense" real\-world knowledge to establish the likelihood of occurrences by using seemingly unlinked attributes\. The node focuses on Tree Augmented Naïve Bayes (TAN) and Marko... | <!doctype html>
<html lang="en-us">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="The Bayesian Network node enables you to build a probability model by c... |
8B5211BC5AC76B26C8C102E576F0AF560DFBCBC2 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/binning.html?context=cdpaas&locale=en | Binning node (SPSS Modeler) | Binning node
The Binning node enables you to automatically create new nominal fields based on the values of one or more existing continuous (numeric range) fields. For example, you can transform a continuous income field into a new categorical field containing income groups of equal width, or as deviations from the ... | # Binning node #
The Binning node enables you to automatically create new nominal fields based on the values of one or more existing continuous (numeric range) fields\. For example, you can transform a continuous income field into a new categorical field containing income groups of equal width, or as deviations from t... | <!doctype html>
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C5673E6023D99F8354E9B61DA2D2F1B58FBC970F | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/c50.html?context=cdpaas&locale=en | C5.0 node (SPSS Modeler) | C5.0 node
This node uses the C5.0 algorithm to build either a decision tree or a rule set. A C5.0 model works by splitting the sample based on the field that provides the maximum information gain. Each sub-sample defined by the first split is then split again, usually based on a different field, and the process repe... | # C5\.0 node #
This node uses the C5\.0 algorithm to build either a decision tree or a rule set\. A C5\.0 model works by splitting the sample based on the field that provides the maximum information gain\. Each sub\-sample defined by the first split is then split again, usually based on a different field, and the proc... | <!doctype html>
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DE6C4CB72844FC59FD80FC0B26ACC8C94A3BA994 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/cache_nodes.html?context=cdpaas&locale=en | Caching options for nodes (SPSS Modeler) | Caching options for nodes
To optimize the running of flows, you can set up a cache on any nonterminal node. When you set up a cache on a node, the cache is filled with the data that passes through the node the next time you run the data flow. From then on, the data is read from the cache (which is stored temporarily... | # Caching options for nodes #
To optimize the running of flows, you can set up a cache on any nonterminal node\. When you set up a cache on a node, the cache is filled with the data that passes through the node the next time you run the data flow\. From then on, the data is read from the cache (which is stored tempora... | <!doctype html>
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D43DE202E6D3EEE211893585616BDA7EB09211C4 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/caml.html?context=cdpaas&locale=en | Continuous machine learning (SPSS Modeler) | Continuous machine learning
As a result of IBM research, and inspired by natural selection in biology, continuous machine learning is available for the Auto Classifier node and the Auto Numeric node.
An inconvenience with modeling is models getting outdated due to changes to your data over time. This is commonly re... | # Continuous machine learning #
As a result of IBM research, and inspired by natural selection in biology, continuous machine learning is available for the Auto Classifier node and the Auto Numeric node\.
An inconvenience with modeling is models getting outdated due to changes to your data over time\. This is commonl... | <!doctype html>
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461D1A8F855174F44550531EF8BE6E67C29D3E3B | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/carma.html?context=cdpaas&locale=en | CARMA node (SPSS Modeler) | CARMA node
The CARMA node uses an association rules discovery algorithm to discover association rules in the data.
Association rules are statements in the form:
if antecedent(s) then consequent(s)
For example, if a Web customer purchases a wireless card and a high-end wireless router, the customer is also like... | # CARMA node #
The CARMA node uses an association rules discovery algorithm to discover association rules in the data\.
Association rules are statements in the form:
if antecedent(s) then consequent(s)
For example, if a Web customer purchases a wireless card and a high\-end wireless router, the customer is a... | <!doctype html>
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37D9428BD2E4A45CA968DAD59D1005FB5FC4DE9C | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/cart.html?context=cdpaas&locale=en | C&R Tree node (SPSS Modeler) | C&R Tree node
The Classification and Regression (C&R) Tree node is a tree-based classification and prediction method. Similar to C5.0, this method uses recursive partitioning to split the training records into segments with similar output field values. The C&R Tree node starts by examining the input fields to find t... | # C&R Tree node #
The Classification and Regression (C&R) Tree node is a tree\-based classification and prediction method\. Similar to C5\.0, this method uses recursive partitioning to split the training records into segments with similar output field values\. The C&R Tree node starts by examining the input fields to ... | <!doctype html>
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D64140C0B8D4187B49046528FF61A54D77A99223 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/chaid.html?context=cdpaas&locale=en | CHAID node (SPSS Modeler) | CHAID node
CHAID, or Chi-squared Automatic Interaction Detection, is a classification method for building decision trees by using chi-square statistics to identify optimal splits.
CHAID first examines the crosstabulations between each of the input fields and the outcome, and tests for significance using a chi-squar... | # CHAID node #
CHAID, or Chi\-squared Automatic Interaction Detection, is a classification method for building decision trees by using chi\-square statistics to identify optimal splits\.
CHAID first examines the crosstabulations between each of the input fields and the outcome, and tests for significance using a chi\... | <!doctype html>
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54EE0BB6FBD2E35C46C41D0065C299408F5AB0A5 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/characters.html?context=cdpaas&locale=en | Characters (SPSS Modeler) | Characters
Characters (usually shown as CHAR) are typically used within a CLEM expression to perform tests on strings.
For example, you can use the function isuppercode to determine whether the first character of a string is uppercase. The following CLEM expression uses a character to indicate that the test should ... | # Characters #
Characters (usually shown as `CHAR`) are typically used within a CLEM expression to perform tests on strings\.
For example, you can use the function `isuppercode` to determine whether the first character of a string is uppercase\. The following CLEM expression uses a character to indicate that the test... | <!doctype html>
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3C1D83E94DDC08D7A6229AEDC49C895E86E660BF | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_datatypes.html?context=cdpaas&locale=en | CLEM datatypes (SPSS Modeler) | CLEM datatypes
This section covers CLEM datatypes.
CLEM datatypes can be made up of any of the following:
* Integers
* Reals
* Characters
* Strings
* Lists
* Fields
* Date/Time
| # CLEM datatypes #
This section covers CLEM datatypes\.
CLEM datatypes can be made up of any of the following:
<!-- <ul> -->
* Integers
* Reals
* Characters
* Strings
* Lists
* Fields
* Date/Time
<!-- </ul> -->
<!-- </article "role="article" "> -->
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6F900078FD88E14400807E571E1F3A24C633C2DC | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_expression_examples.html?context=cdpaas&locale=en | CLEM examples (SPSS Modeler) | CLEM examples
The example expressions in this section illustrate correct syntax and the types of expressions possible with CLEM.
Additional examples are discussed throughout this CLEM documentation. See [CLEM (legacy) language reference](https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_... | # CLEM examples #
The example expressions in this section illustrate correct syntax and the types of expressions possible with CLEM\.
Additional examples are discussed throughout this CLEM documentation\. See [CLEM (legacy) language reference](https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/c... | <!doctype html>
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628354B3F2FA792B938756225315E3B4024DCC0E | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref.html?context=cdpaas&locale=en | Functions reference (SPSS Modeler) | Functions reference
This section lists CLEM functions for working with data in SPSS Modeler. You can enter these functions as code in various areas of the user interface, such as Derive and Set To Flag nodes, or you can use the Expression Builder to create valid CLEM expressions without memorizing function lists or ... | # Functions reference #
This section lists CLEM functions for working with data in SPSS Modeler\. You can enter these functions as code in various areas of the user interface, such as Derive and Set To Flag nodes, or you can use the Expression Builder to create valid CLEM expressions without memorizing function lists ... | <!doctype html>
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1D1659B46A454170A597B0450FD99C16EEC5B1AD | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_bitwise.html?context=cdpaas&locale=en | Bitwise integer operations (SPSS Modeler) | Bitwise integer operations
These functions enable integers to be manipulated as bit patterns representing two's-complement values, where bit position N has weight 2N.
Bits are numbered from 0 upward. These operations act as though the sign bit of an integer is extended indefinitely to the left. Thus, everywhere abo... | # Bitwise integer operations #
These functions enable integers to be manipulated as bit patterns representing two's\-complement values, where bit position `N` has weight `2**N`\.
Bits are numbered from 0 upward\. These operations act as though the sign bit of an integer is extended indefinitely to the left\. Thus, ev... | <!doctype html>
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5FE3DE32EFB5DEA4094DCA22CBC77E24D23EF67A | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_blanksnulls.html?context=cdpaas&locale=en | Functions handling blanks and null values (SPSS Modeler) | Functions handling blanks and null values
Using CLEM, you can specify that certain values in a field are to be regarded as "blanks," or missing values.
The following functions work with blanks.
CLEM blank and null value functions
Table 1. CLEM blank and null value functions
Function Result ... | # Functions handling blanks and null values #
Using CLEM, you can specify that certain values in a field are to be regarded as "blanks," or missing values\.
The following functions work with blanks\.
<!-- <table "summary="CLEM blank and null value functions" id="clem_function_ref_blanksnulls__table_shj_4k3_cdb" clas... | <!doctype html>
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32A79D23C94FB1920DB500D2DD9464C1316C62A5 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_comparison.html?context=cdpaas&locale=en | Comparison functions (SPSS Modeler) | Comparison functions
Comparison functions are used to compare field values to each other or to a specified string.
For example, you can check strings for equality using =. An example of string equality verification is: Class = "class 1".
For purposes of numeric comparison, greater means closer to positive infinity... | # Comparison functions #
Comparison functions are used to compare field values to each other or to a specified string\.
For example, you can check strings for equality using `=`\. An example of string equality verification is: `Class = "class 1"`\.
For purposes of numeric comparison, *greater* means closer to positi... | <!doctype html>
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8CE325D8AFC27359968A8799D58EF4BF0C57D68E | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_conversion.html?context=cdpaas&locale=en | Conversion functions (SPSS Modeler) | Conversion functions
With conversion functions, you can construct new fields and convert the storage type of existing files.
For example, you can form new strings by joining strings together or by taking strings apart. To join two strings, use the operator ><. For example, if the fieldSite has the value"BRAMLEY", t... | # Conversion functions #
With conversion functions, you can construct new fields and convert the storage type of existing files\.
For example, you can form new strings by joining strings together or by taking strings apart\. To join two strings, use the operator `><`\. For example, if the field`Site` has the value`"B... | <!doctype html>
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D1FAFA3A73F77B401F49CC641BE44D61BC9C0689 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_datetime.html?context=cdpaas&locale=en | Date and time functions (SPSS Modeler) | Date and time functions
CLEM includes a family of functions for handling fields with datetime storage of string variables representing dates and times.
The formats of date and time used are specific to each flow and are specified in the flow properties. The date and time functions parse date and time strings accord... | # Date and time functions #
CLEM includes a family of functions for handling fields with datetime storage of string variables representing dates and times\.
The formats of date and time used are specific to each flow and are specified in the flow properties\. The date and time functions parse date and time strings ac... | <!doctype html>
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299CEE894DFF422AAC8BF49B53CAC700DE1B172D | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_global.html?context=cdpaas&locale=en | Global functions (SPSS Modeler) | Global functions
The functions @MEAN, @SUM, @MIN, @MAX, and @SDEV work on, at most, all of the records read up to and including the current one. In some cases, however, it is useful to be able to work out how values in the current record compare with values seen in the entire data set. Using a Set Globals node to ge... | # Global functions #
The functions `@MEAN`, `@SUM`, `@MIN`, `@MAX`, and `@SDEV` work on, at most, all of the records read up to and including the current one\. In some cases, however, it is useful to be able to work out how values in the current record compare with values seen in the entire data set\. Using a Set Glob... | <!doctype html>
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C6379E4ACDD7B1C335E9944B8D9DBB08DB220420 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_information.html?context=cdpaas&locale=en | Information functions (SPSS Modeler) | Information functions
You can use information functions to gain insight into the values of a particular field. They're typically used to derive flag fields.
For example, the @BLANK function creates a flag field indicating records whose values are blank for the selected field. Similarly, you can check the storage ty... | # Information functions #
You can use information functions to gain insight into the values of a particular field\. They're typically used to derive flag fields\.
For example, the `@BLANK` function creates a flag field indicating records whose values are blank for the selected field\. Similarly, you can check the sto... | <!doctype html>
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A67EA42903BF8BE22AEB379891B7E1CA3EB2E4D1 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_logical.html?context=cdpaas&locale=en | Logical functions (SPSS Modeler) | Logical functions
CLEM expressions can be used to perform logical operations.
CLEM logical functions
Table 1. CLEM logical functions
Function Result Description ... | # Logical functions #
CLEM expressions can be used to perform logical operations\.
<!-- <table "summary="CLEM logical functions" id="clem_function_ref_logical__table_bct_5k3_cdb" class="defaultstyle" "> -->
CLEM logical functions
Table 1\. CLEM logical functions
| Function ... | <!doctype html>
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EEC0EB0502DEF7B7ADB112F8D7D4C38E1F6D9170 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_numeric.html?context=cdpaas&locale=en | Numeric functions (SPSS Modeler) | Numeric functions
CLEM contains a number of commonly used numeric functions.
CLEM numeric functions
Table 1. CLEM numeric functions
Function Result Description ... | # Numeric functions #
CLEM contains a number of commonly used numeric functions\.
<!-- <table "summary="CLEM numeric functions" id="clem_function_ref_numeric__table_dw4_qqz_ddb" class="defaultstyle" "> -->
CLEM numeric functions
Table 1\. CLEM numeric functions
| Function | Result | Description ... | <!doctype html>
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29DEEC30687F805460A83DD924D2F119274D25F8 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_probability.html?context=cdpaas&locale=en | Probability functions (SPSS Modeler) | Probability functions
Probability functions return probabilities based on various distributions, such as the probability that a value from Student's t distribution will be less than a specific value.
CLEM probability functions
Table 1. CLEM probability functions
Function Result Descrip... | # Probability functions #
Probability functions return probabilities based on various distributions, such as the probability that a value from Student's *t* distribution will be less than a specific value\.
<!-- <table "summary="CLEM probability functions" id="clem_function_ref_probability__table_vqh_xk3_cdb" class="... | <!doctype html>
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9789F3A8936AD06C653C1C7AEB421C70FFD7C3E1 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_random.html?context=cdpaas&locale=en | Random functions (SPSS Modeler) | Random functions
The functions listed on this page can be used to randomly select items or randomly generate numbers.
CLEM random functions
Table 1. CLEM random functions
Function Result Description ... | # Random functions #
The functions listed on this page can be used to randomly select items or randomly generate numbers\.
<!-- <table "summary="CLEM random functions" id="clem_function_ref_random__table_t2w_sqz_ddb" class="defaultstyle" "> -->
CLEM random functions
Table 1\. CLEM random functions
| Function ... | <!doctype html>
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BACAF30043E33912E3D7F174B3F8CF858CB3093A | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_sequence.html?context=cdpaas&locale=en | Sequence functions (SPSS Modeler) | Sequence functions
For some operations, the sequence of events is important.
The application allows you to work with the following record sequences:
* Sequences and time series
* Sequence functions
* Record indexing
* Averaging, summing, and comparing values
* Monitoring change—differentiation
* @SINCE
* ... | # Sequence functions #
For some operations, the sequence of events is important\.
The application allows you to work with the following record sequences:
<!-- <ul> -->
* Sequences and time series
* Sequence functions
* Record indexing
* Averaging, summing, and comparing values
* Monitoring change—differen... | <!doctype html>
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88E4E066B89D0A6993F31EA337930D962B76D6D1 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_soundex.html?context=cdpaas&locale=en | SoundEx functions (SPSS Modeler) | SoundEx functions
SoundEx is a method used to find strings when the sound is known but the precise spelling isn't known.
Developed in 1918, the method searches out words with similar sounds based on phonetic assumptions about how certain letters are pronounced. SoundEx can be used to search names in a database (for... | # SoundEx functions #
SoundEx is a method used to find strings when the sound is known but the precise spelling isn't known\.
Developed in 1918, the method searches out words with similar sounds based on phonetic assumptions about how certain letters are pronounced\. SoundEx can be used to search names in a database ... | <!doctype html>
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2C0EBF0CCB497F41C14A5895EF97C01864BFC3D2 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_spatial.html?context=cdpaas&locale=en | Spatial functions (SPSS Modeler) | Spatial functions
Spatial functions can be used with geospatial data. For example, they allow you to calculate the distances between two points, the area of a polygon, and so on.
There can also be situations that require a merge of multiple geospatial data sets that are based on a spatial predicate (within, close t... | # Spatial functions #
Spatial functions can be used with geospatial data\. For example, they allow you to calculate the distances between two points, the area of a polygon, and so on\.
There can also be situations that require a merge of multiple geospatial data sets that are based on a spatial predicate (within, clo... | <!doctype html>
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4058D0B5222F1C34ABF1737A10DA705E27480606 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_specialfields.html?context=cdpaas&locale=en | Special fields (SPSS Modeler) | Special fields
Special functions are used to denote the specific fields under examination, or to generate a list of fields as input.
For example, when deriving multiple fields at once, you should use @FIELD to denote perform this derive action on the selected fields. Using the expression log(@FIELD) derives a new l... | # Special fields #
Special functions are used to denote the specific fields under examination, or to generate a list of fields as input\.
For example, when deriving multiple fields at once, you should use `@FIELD` to denote perform this derive action on the selected fields\. Using the expression `log(@FIELD)` derives... | <!doctype html>
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9A83A33ABB4C6A12A7457D3711C2511EB3982B2C | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_string.html?context=cdpaas&locale=en | String functions (SPSS Modeler) | String functions
With CLEM, you can run operations to compare strings, create strings, or access characters.
In CLEM, a string is any sequence of characters between matching double quotation marks ("string quotes"). Characters (CHAR) can be any single alphanumeric character. They're declared in CLEM expressions usi... | # String functions #
With CLEM, you can run operations to compare strings, create strings, or access characters\.
In CLEM, a string is any sequence of characters between matching double quotation marks (`"string quotes"`)\. Characters (`CHAR`) can be any single alphanumeric character\. They're declared in CLEM expres... | <!doctype html>
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2904E26946523BB3E78975F68A822F5F2A32B9F5 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_function_ref_trigonometric.html?context=cdpaas&locale=en | Trigonometric functions (SPSS Modeler) | Trigonometric functions
All of the functions in this section either take an angle as an argument or return one as a result.
CLEM trigonometric functions
Table 1. CLEM trigonometric functions
Function Result Description ... | # Trigonometric functions #
All of the functions in this section either take an angle as an argument or return one as a result\.
<!-- <table "summary="CLEM trigonometric functions" id="clem_function_ref_trigonometric__table_ih3_dl3_cdb" class="defaultstyle" "> -->
CLEM trigonometric functions
Table 1\. CLEM trigo... | <!doctype html>
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621083EB36CF3896B77D22EDBCC23FD2716F6B4A | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_functions_convertingdates.html?context=cdpaas&locale=en | Converting date and time values (SPSS Modeler) | Converting date and time values
Note that conversion functions (and any other functions that require a specific type of input, such as a date or time value) depend on the current formats specified in the flow properties.
For example, if you have a field named DATE that's stored as a string with values Jan 2021, Feb... | # Converting date and time values #
Note that conversion functions (and any other functions that require a specific type of input, such as a date or time value) depend on the current formats specified in the flow properties\.
For example, if you have a field named *DATE* that's stored as a string with values *Jan 202... | <!doctype html>
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ADBEF9D5635EB271A8BD78B23064DCBA1A1915A6 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_language_reference.html?context=cdpaas&locale=en | CLEM language reference (SPSS Modeler) | CLEM (legacy) language reference
This section describes the Control Language for Expression Manipulation (CLEM), which is a powerful tool used to analyze and manipulate the data used in SPSS Modeler flows.
You can use CLEM within nodes to perform tasks ranging from evaluating conditions or deriving values to insert... | # CLEM (legacy) language reference #
This section describes the Control Language for Expression Manipulation (CLEM), which is a powerful tool used to analyze and manipulate the data used in SPSS Modeler flows\.
You can use CLEM within nodes to perform tasks ranging from evaluating conditions or deriving values to ins... | <!doctype html>
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88467827811ED045A648A3C215F5B91D43EB49CD | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_overview_multiple_response_data.html?context=cdpaas&locale=en | Working with multiple-response data (SPSS Modeler) | Working with multiple-response data
You can analyze multiple-response data using a number of comparison functions.
Available comparison functions include:
* value_at
* first_index / last_index
* first_non_null / last_non_null
* first_non_null_index / last_non_null_index
* min_index / max_index
For exampl... | # Working with multiple\-response data #
You can analyze multiple\-response data using a number of comparison functions\.
Available comparison functions include:
<!-- <ul> -->
* `value_at`
* `first_index / last_index`
* `first_non_null / last_non_null`
* `first_non_null_index / last_non_null_index`
* `min... | <!doctype html>
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BC314650433831859C400BFFEFE5F919ED8735EA | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_overview_numbers.html?context=cdpaas&locale=en | Working with numbers (SPSS Modeler) | Working with numbers
Numerous standard operations on numeric values are available in SPSS Modeler.
* Calculating the sine of the specified angle—sin(NUM)
* Calculating the natural log of numeric fields—log(NUM)
* Calculating the sum of two numbers—NUM1 + NUM2
See [Numeric functions](https://dataplatform.clo... | # Working with numbers #
Numerous standard operations on numeric values are available in SPSS Modeler\.
<!-- <ul> -->
* Calculating the sine of the specified angle—`sin(NUM)`
* Calculating the natural log of numeric fields—`log(NUM)`
* Calculating the sum of two numbers—`NUM1` \+ `NUM2`
<!-- </ul> -->
See [N... | <!doctype html>
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595BB1738027C777C1EB5A69631587923690ABC4 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_overview_times_and_dates.html?context=cdpaas&locale=en | Working with strings (SPSS Modeler) | Working with strings
There are a number of operations available for strings.
* Converting a string to uppercase or lowercase—uppertolower(CHAR).
* Removing specified characters, such as ID_ or $ , from a string variable—stripchar(CHAR,STRING).
* Determining the length (number of characters) for a string var... | # Working with strings #
There are a number of operations available for strings\.
<!-- <ul> -->
* Converting a string to uppercase or lowercase—`uppertolower(CHAR)`\.
* Removing specified characters, such as `` `ID_` `` or `` `$` ``, from a string variable—`stripchar(CHAR,STRING)`\.
* Determining the length (n... | <!doctype html>
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<meta name=... |
D1FEF8C7F5BE28316CAA952CCC76281E6F3FE12F | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_summarizemultiplefields.html?context=cdpaas&locale=en | Summarizing multiple fields (SPSS Modeler) | Summarizing multiple fields
The CLEM language includes a number of functions that return summary statistics across multiple fields.
These functions may be particularly useful in analyzing survey data, where multiple responses to a question may be stored in multiple fields. See [Working with multiple-response data](... | # Summarizing multiple fields #
The CLEM language includes a number of functions that return summary statistics across multiple fields\.
These functions may be particularly useful in analyzing survey data, where multiple responses to a question may be stored in multiple fields\. See [Working with multiple\-response d... | <!doctype html>
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DAD2EDE59535330241F2FEBDF9BF99E21DEB4393 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clem_times_and_dates_uses.html?context=cdpaas&locale=en | Working with times and dates (SPSS Modeler) | Working with times and dates
Time and date formats may vary depending on your data source and locale. The formats of date and time are specific to each flow and are set in the flow properties.
The following examples are commonly used functions for working with date/time fields.
| # Working with times and dates #
Time and date formats may vary depending on your data source and locale\. The formats of date and time are specific to each flow and are set in the flow properties\.
The following examples are commonly used functions for working with date/time fields\.
<!-- </article "role="article" ... | <!doctype html>
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0F686BF5943844896A5385E01D440548081D2688 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clemoverview_blanksnulls.html?context=cdpaas&locale=en | Handling blanks and missing values (SPSS Modeler) | Handling blanks and missing values
Replacing blanks or missing values is a common data preparation task for data miners. CLEM provides you with a number of tools to automate blank handling.
The Filler node is the most common place to work with blanks; however, the following functions can be used in any node that ac... | # Handling blanks and missing values #
Replacing blanks or missing values is a common data preparation task for data miners\. CLEM provides you with a number of tools to automate blank handling\.
The Filler node is the most common place to work with blanks; however, the following functions can be used in any node tha... | <!doctype html>
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23296AAD76933152D5D3E9DD875EBBD3FB7575EA | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/clemoverview_container.html?context=cdpaas&locale=en | Building CLEM expressions (SPSS Modeler) | Building CLEM (legacy) expressions
| # Building CLEM (legacy) expressions #
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7B9348596E2F005F89842D1B997FA09BDCBE8F06 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/conventions_in_function_descriptions.html?context=cdpaas&locale=en | Conventions and function descriptions (SPSS Modeler) | Conventions in function descriptions
This page describes the conventions used throughout this guide when referring to items in a function.
Conventions in function descriptions
Table 1. Conventions in function descriptions
Convention Description ... | # Conventions in function descriptions #
This page describes the conventions used throughout this guide when referring to items in a function\.
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Conventions in function ... | <!doctype html>
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C2185A8C9156C6B38D76BD3FD29A833D96A5762B | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/date_formats.html?context=cdpaas&locale=en | Dates (SPSS Modeler) | Dates
Date calculations are based on a "baseline" date, which is specified in the flow properties. The default baseline date is 1 January 1900.
The CLEM language supports the following date formats.
CLEM language date formats
Table 1. CLEM language date formats
Format Examples ... | # Dates #
Date calculations are based on a "baseline" date, which is specified in the flow properties\. The default baseline date is 1 January 1900\.
The CLEM language supports the following date formats\.
<!-- <table "summary="CLEM language date formats" id="date_formats__table_a1p_3bj_cdb" class="defaultstyle" "> ... | <!doctype html>
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FE88457CA86FFE3BE30873156A7A0A4FD12975AF | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/ebuilder_accessing.html?context=cdpaas&locale=en | Accessing the Expression Builder (SPSS Modeler) | Accessing the Expression Builder
The Expression Builder is available in all nodes where CLEM expressions are used, including Select, Balance, Derive, Filler, Analysis, Report, and Table nodes.
You can open it by double-clicking the node to open its properties, then click the calculator button by the formula field.
... | # Accessing the Expression Builder #
The Expression Builder is available in all nodes where CLEM expressions are used, including Select, Balance, Derive, Filler, Analysis, Report, and Table nodes\.
You can open it by double\-clicking the node to open its properties, then click the calculator button by the formula fie... | <!doctype html>
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56EA4620B049A9E291BF198E71D0C58C2018686D | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/ebuilder_checking.html?context=cdpaas&locale=en | Checking CLEM expressions (SPSS Modeler) | Checking CLEM expressions
Click Validate in the Expression Builder to validate an expression.
Expressions that haven't been checked are displayed in red. If errors are found, a message indicating the cause is displayed.
The following items are checked:
* Correct quoting of values and field names
* Correct us... | # Checking CLEM expressions #
Click Validate in the Expression Builder to validate an expression\.
Expressions that haven't been checked are displayed in red\. If errors are found, a message indicating the cause is displayed\.
The following items are checked:
<!-- <ul> -->
* Correct quoting of values and field ... | <!doctype html>
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... |
6FD8A950F1EBE6B021EA9D4C775A5CA8660A1101 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/ebuilder_using.html?context=cdpaas&locale=en | Creating expressions (SPSS Modeler) | Creating expressions
The Expression Builder provides not only complete lists of fields, functions, and operators but also access to data values if your data is instantiated.
| # Creating expressions #
The Expression Builder provides not only complete lists of fields, functions, and operators but also access to data values if your data is instantiated\.
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| <!doctype html>
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B8044B03933E3FCEA5BCF6362199ED083EC2F20F | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/expressionbuild_database_functions.html?context=cdpaas&locale=en | Database functions (SPSS Modeler) | Database functions
You can run an SPSS Modeler desktop stream file ( .str) that contains database functions.
But database functions aren't available in the Expression Builder user interface, and you can't edit them.
| # Database functions #
You can run an SPSS Modeler desktop stream file ( \.str) that contains database functions\.
But database functions aren't available in the Expression Builder user interface, and you can't edit them\.
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841465AD74B0AFDBEC9EAFF7B038AFC4C000E96C | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/expressionbuild_fields.html?context=cdpaas&locale=en | Selecting fields (SPSS Modeler) | Selecting fields
The field list displays all fields available at this point in the data stream. Double-click a field from the list to add it to your expression.
After selecting a field, you can also select an associated value from the value list.
| # Selecting fields #
The field list displays all fields available at this point in the data stream\. Double\-click a field from the list to add it to your expression\.
After selecting a field, you can also select an associated value from the value list\.
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0093065541AA4C3E90E47E3ACE89596155EA1735 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/expressionbuild_functions.html?context=cdpaas&locale=en | Selecting functions (SPSS Modeler) | Selecting functions
The function list displays all available SPSS Modeler functions and operators. Scroll to select a function from the list, or, for easier searching, use the drop-down list to display a subset of functions or operators. Available functions are grouped into categories for easier searching.
Most of ... | # Selecting functions #
The function list displays all available SPSS Modeler functions and operators\. Scroll to select a function from the list, or, for easier searching, use the drop\-down list to display a subset of functions or operators\. Available functions are grouped into categories for easier searching\.
Mo... | <!doctype html>
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C89753519B91F85DC9E0ED54A3248CD82D5F2A9E | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/expressionbuilderdialog.html?context=cdpaas&locale=en | The Expression Builder (SPSS Modeler) | The Expression Builder
You can type CLEM expressions manually or use the Expression Builder, which displays a complete list of CLEM functions and operators as well as data fields from the current flow, allowing you to quickly build expressions without memorizing the exact names of fields or functions.
In addition, ... | # The Expression Builder #
You can type CLEM expressions manually or use the Expression Builder, which displays a complete list of CLEM functions and operators as well as data fields from the current flow, allowing you to quickly build expressions without memorizing the exact names of fields or functions\.
In additio... | <!doctype html>
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F4F623D5A7C8913E227E962BD1F347B36AAB7B51 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/expressions_and_conditions.html?context=cdpaas&locale=en | Expressions and conditions (SPSS Modeler) | Expressions and conditions
CLEM expressions can return a result (used when deriving new values).
For example:
Weight * 2.2
Age + 1
sqrt(Signal-Echo)
Or, they can evaluate true or false (used when selecting on a condition). For example:
Drug = "drugA"
Age < 16
not(PowerFlux) and Power > 2000
You can combine oper... | # Expressions and conditions #
CLEM expressions can return a result (used when deriving new values)\.
For example:
Weight * 2.2
Age + 1
sqrt(Signal-Echo)
Or, they can evaluate *true* or *false* (used when selecting on a condition)\. For example:
Drug = "drugA"
Age < 16
not(PowerFlux) and Po... | <!doctype html>
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85F8B4292483C5747AB2436A2D5D5377F1F6CAB9 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/field_information.html?context=cdpaas&locale=en | Viewing or selecting values (SPSS Modeler) | Viewing or selecting values
You can view field values from the Expression Builder. Note that data must be fully instantiated in an Import or Type node to use this feature, so that storage, types, and values are known.
To view values for a field from the Expression Builder, select the required field and then use the... | # Viewing or selecting values #
You can view field values from the Expression Builder\. Note that data must be fully instantiated in an Import or Type node to use this feature, so that storage, types, and values are known\.
To view values for a field from the Expression Builder, select the required field and then use... | <!doctype html>
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B69246113E589F088E8E1302B32B57720BD27720 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/fields.html?context=cdpaas&locale=en | Fields (SPSS Modeler) | Fields
Names in CLEM expressions that aren’t names of functions are assumed to be field names.
You can write these simply as Power, val27, state_flag, and so on, but if the name begins with a digit or includes non-alphabetic characters, such as spaces (with the exception of the underscore), place the name within si... | # Fields #
Names in CLEM expressions that aren’t names of functions are assumed to be field names\.
You can write these simply as `Power`, `val27`, `state_flag`, and so on, but if the name begins with a digit or includes non\-alphabetic characters, such as spaces (with the exception of the underscore), place the name... | <!doctype html>
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C528D240892080AECE146D29FB3496DDD0F1FD48 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/findreplacedialog.html?context=cdpaas&locale=en | Find (SPSS Modeler) | Find
In the Expression Builder, you can search for fields, values, or functions.
For example, to search for a value, place your cursor in the Find in column Value field and enter the text you want to search for.
You can also search on special characters such as tabs or newline characters, classes or ranges of cha... | # Find #
In the Expression Builder, you can search for fields, values, or functions\.
For example, to search for a value, place your cursor in the Find in column Value field and enter the text you want to search for\.
You can also search on special characters such as tabs or newline characters, classes or ranges of... | <!doctype html>
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C1324A359A58B4D399C10BC59AE94E7E0723836D | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/integers.html?context=cdpaas&locale=en | Integers (SPSS Modeler) | Integers
Integers are represented as a sequence of decimal digits.
Optionally, you can place a minus sign (−) before the integer to denote a negative number (for example, 1234, 999, −77).
The CLEM language handles integers of arbitrary precision. The maximum integer size depends on your platform. If the values are... | # Integers #
Integers are represented as a sequence of decimal digits\.
Optionally, you can place a minus sign (−) before the integer to denote a negative number (for example, `1234`, `999`, −`77`)\.
The CLEM language handles integers of arbitrary precision\. The maximum integer size depends on your platform\. If th... | <!doctype html>
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<head>
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<meta name="description" content="Integers are represented as a sequence of decimal digits.">
<meta nam... |
D05F366AFC5726DC1A258EDC3689067381EFDECC | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/introduction_to_clem.html?context=cdpaas&locale=en | About CLEM (SPSS Modeler) | About CLEM
The Control Language for Expression Manipulation (CLEM) is a powerful language for analyzing and manipulating the data that streams through an SPSS Modeler flow. Data miners use CLEM extensively in flow operations to perform tasks as simple as deriving profit from cost and revenue data or as complex as tr... | # About CLEM #
The Control Language for Expression Manipulation (CLEM) is a powerful language for analyzing and manipulating the data that streams through an SPSS Modeler flow\. Data miners use CLEM extensively in flow operations to perform tasks as simple as deriving profit from cost and revenue data or as complex as... | <!doctype html>
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<meta name="description" content="The Control Language for Expression Manipulation (CLEM) is a powerful l... |
B93F8A3A1CED22CF84C45B552D5040A4A17FDB60 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/lists.html?context=cdpaas&locale=en | Lists (SPSS Modeler) | Lists
A list is an ordered sequence of elements, which may be of mixed type. Lists are enclosed in square brackets ([ ]).
Examples of lists are [1 2 4 16] and ["abc" "def"] and [A1, A2, A3]. Lists are not used as the value of SPSS Modeler fields. They are used to provide arguments to functions, such as member and o... | # Lists #
A list is an ordered sequence of elements, which may be of mixed type\. Lists are enclosed in square brackets (\[ \])\.
Examples of lists are `[1 2 4 16]` and `["abc" "def"]` and `[A1, A2, A3]`\. Lists are not used as the value of SPSS Modeler fields\. They are used to provide arguments to functions, such a... | <!doctype html>
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9455A31E5D6C749F3028F9F5E5F758F713C09973 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/operator_precedence.html?context=cdpaas&locale=en | CLEM operators (SPSS Modeler) | CLEM operators
This page lists the available CLEM language operators.
CLEM language operators
Table 1. CLEM language operators
Operation Comments Precedence (see next section)
or Used be... | # CLEM operators #
This page lists the available CLEM language operators\.
<!-- <table "summary="CLEM language operators" id="operator_precedence__table_gt3_lwz_ddb" class="defaultstyle" "> -->
CLEM language operators
Table 1\. CLEM language operators
| Operation | Comments ... | <!doctype html>
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<meta name="... |
185C42AB06DE9FF515DCD03213F5C4608C6FAEBF | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/reals.html?context=cdpaas&locale=en | Reals (SPSS Modeler) | Reals
Real refers to a floating-point number. Reals are represented by one or more digits followed by a decimal point followed by one or more digits. CLEM reals are held in double precision.
Optionally, you can place a minus sign (−) before the real to denote a negative number (for example, 1.234, 0.999, −77.001). ... | # Reals #
*Real* refers to a floating\-point number\. Reals are represented by one or more digits followed by a decimal point followed by one or more digits\. CLEM reals are held in double precision\.
Optionally, you can place a minus sign (−) before the real to denote a negative number (for example, `1.234`, `0.999`... | <!doctype html>
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385DEC32600A9DED58FEDE3E98568FED789A400A | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/strings.html?context=cdpaas&locale=en | Strings (SPSS Modeler) | Strings
Generally, you should enclose strings in double quotation marks. Examples of strings are "c35product2" and "referrerID".
To indicate special characters in a string, use a backslash (for example, "$65443"). (To indicate a backslash character, use a double backslash, \.) You can use single quotes around a str... | # Strings #
Generally, you should enclose strings in double quotation marks\. Examples of strings are `"c35product2"` and `"referrerID"`\.
To indicate special characters in a string, use a backslash (for example, `"\$65443"`)\. (To indicate a backslash character, use a double backslash, `\\`\.) You can use single quo... | <!doctype html>
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="Generally, you should enclose strings in double quotation marks. Exampl... |
839B16AC73C000ECE7BAC7D50BAF6F7E37F2CAD9 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/time_formats_clem_language.html?context=cdpaas&locale=en | Time (SPSS Modeler) | Time
The CLEM language supports the time formats listed in this section.
CLEM language time formats
Table 1. CLEM language time formats
Format Examples
HHMMSS 120112, 010101, 221212
HHMM 1223, 0745, 2207
MMSS 555... | # Time #
The CLEM language supports the time formats listed in this section\.
<!-- <table "summary="CLEM language time formats" id="time_formats_clem_language__table_zbw_jyy_ddb" class="defaultstyle" "> -->
CLEM language time formats
Table 1\. CLEM language time formats
| Format | Examples ... | <!doctype html>
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... |
F975B9964D088181CF34A1341083BC82053812D8 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/clem_reference/values_and_data_types.html?context=cdpaas&locale=en | Values and data types (SPSS Modeler) | Values and data types
CLEM expressions are similar to formulas constructed from values, field names, operators, and functions. The simplest valid CLEM expression is a value or a field name.
Examples of valid values are:
3
1.79
'banana'
Examples of field names are:
Product_ID
'$P-NextField'
where Product is the ... | # Values and data types #
CLEM expressions are similar to formulas constructed from values, field names, operators, and functions\. The simplest valid CLEM expression is a value or a field name\.
Examples of valid values are:
3
1.79
'banana'
Examples of field names are:
Product_ID
'$P-NextField... | <!doctype html>
<html lang="en-us">
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<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="CLEM expressions are similar to formulas constructed from values, field... |
EE838EA978F9A0B0265A8D2B35FF2F64D00A1738 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/collection.html?context=cdpaas&locale=en | Collection node (SPSS Modeler) | Collection node
Collections are similar to histograms, but collections show the distribution of values for one numeric field relative to the values of another, rather than the occurrence of values for a single field. A collection is useful for illustrating a variable or field whose values change over time.
Using 3-... | # Collection node #
Collections are similar to histograms, but collections show the distribution of values for one numeric field relative to the values of another, rather than the occurrence of values for a single field\. A collection is useful for illustrating a variable or field whose values change over time\.
Usin... | <!doctype html>
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<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
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<meta name="description" content="Collections are similar to histograms, but collections show the distrib... |
5A8AA187972BA8A711AC91447F668B233E580C8C | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/coxreg.html?context=cdpaas&locale=en | Cox node (SPSS Modeler) | Cox node
Cox Regression builds a predictive model for time-to-event data. The model produces a survival function that predicts the probability that the event of interest has occurred at a given time t for given values of the predictor variables. The shape of the survival function and the regression coefficients for ... | # Cox node #
Cox Regression builds a predictive model for time\-to\-event data\. The model produces a survival function that predicts the probability that the event of interest has occurred at a given time `t` for given values of the predictor variables\. The shape of the survival function and the regression coefficie... | <!doctype html>
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<meta name="description" content="Cox Regression builds a predictive model for time-to-event data. The mo... |
67B99E436854F015A9DB19C775639BA4BB4D5F9B | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/cplex.html?context=cdpaas&locale=en | CPLEX Optimization node (SPSS Modeler) | CPLEX Optimization node
With the CPLEX Optimization node, you can use complex mathematical (CPLEX) based optimization via an Optimization Programming Language (OPL) model file.
For more information about CPLEX optimization and OPL, see the [IBM ILOG CPLEX Optimization Studio documentation](https://www.ibm.com/suppo... | # CPLEX Optimization node #
With the CPLEX Optimization node, you can use complex mathematical (CPLEX) based optimization via an Optimization Programming Language (OPL) model file\.
For more information about CPLEX optimization and OPL, see the [IBM ILOG CPLEX Optimization Studio documentation](https://www.ibm.com/su... | <!doctype html>
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<meta name="description" content="With the CPLEX Optimization node, you can use complex mathematical (CPL... |
9FA71067981E4FC0D6F68A14C91C694DC4C2AF25 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/dataassetexport.html?context=cdpaas&locale=en | Data Asset Export node (SPSS Modeler) | Data Asset Export node
You can use the Data Asset Export node to write to remote data sources using connections or write data to a project (delimited or . sav).
Double-click the node to open its properties. Various options are available, described as follows.
After running the node, you can find the data at the ex... | # Data Asset Export node #
You can use the Data Asset Export node to write to remote data sources using connections or write data to a project (delimited or \. sav)\.
Double\-click the node to open its properties\. Various options are available, described as follows\.
After running the node, you can find the data at... | <!doctype html>
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
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C70BB33E4E6792511DC4E7D88536017E64BCD0F1 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/dataassetimport.html?context=cdpaas&locale=en | Data Asset node (SPSS Modeler) | Data Asset node
You can use the Data Asset import node to pull in data from remote data sources using connections or from your local computer. First, you must create the connection.
Note for connections to a Planning Analytics database, you must choose a view (not a cube).
You can also pull in data from a local da... | # Data Asset node #
You can use the Data Asset import node to pull in data from remote data sources using connections or from your local computer\. First, you must create the connection\.
Note for connections to a Planning Analytics database, you must choose a view (not a cube)\.
You can also pull in data from a loc... | <!doctype html>
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<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="You can use the Data Asset import node to pull in data from remote data... |
7F4648FD3E7F8564C98CF142E0E09E23E8097A9E | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/dataaudit.html?context=cdpaas&locale=en | Data Audit node (SPSS Modeler) | Data Audit node
The Data Audit node provides a comprehensive first look at the data you bring to SPSS Modeler, presented in an interactive, easy-to-read matrix that can be sorted and used to generate full-size graphs.
When you run a Data Audit node, interactive output is generated that includes:
* Information ... | # Data Audit node #
The Data Audit node provides a comprehensive first look at the data you bring to SPSS Modeler, presented in an interactive, easy\-to\-read matrix that can be sorted and used to generate full\-size graphs\.
When you run a Data Audit node, interactive output is generated that includes:
<!-- <ul> -... | <!doctype html>
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<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="The Data Audit node provides a comprehensive first look at the data you... |
1A5F15E64AABDCA9E2785588E76F3EBE22A1C426 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/decisionlist.html?context=cdpaas&locale=en | Decision List node (SPSS Modeler) | Decision List node
Decision List models identify subgroups or segments that show a higher or lower likelihood of a binary (yes or no) outcome relative to the overall sample.
For example, you might look for customers who are least likely to churn or most likely to say yes to a particular offer or campaign. The Decis... | # Decision List node #
Decision List models identify subgroups or segments that show a higher or lower likelihood of a binary (yes or no) outcome relative to the overall sample\.
For example, you might look for customers who are least likely to churn or most likely to say yes to a particular offer or campaign\. The D... | <!doctype html>
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<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="Decision List models identify subgroups or segments that show a higher ... |
4D299EFFF5B982097A5B9D48EA16041E4820A8BB | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/derive.html?context=cdpaas&locale=en | Derive node (SPSS Modeler) | Derive node
One of the most powerful features in watsonx.ai is the ability to modify data values and derive new fields from existing data. During lengthy data mining projects, it is common to perform several derivations, such as extracting a customer ID from a string of Web log data or creating a customer lifetime ... | # Derive node #
One of the most powerful features in watsonx\.ai is the ability to modify data values and derive new fields from existing data\. During lengthy data mining projects, it is common to perform several derivations, such as extracting a customer ID from a string of Web log data or creating a customer lifet... | <!doctype html>
<html lang="en-us">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="One of the most powerful features in watsonx.ai is the ability to modif... |
20CFE34D5494AB0AE2EF8B6F65396EDBF667F688 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/derive_stb.html?context=cdpaas&locale=en | Space-Time-Boxes node (SPSS Modeler) | Space-Time-Boxes node
Space-Time-Boxes (STB) are an extension of Geohashed spatial locations. More specifically, an STB is an alphanumeric string that represents a regularly shaped region of space and time.
For example, the STB dr5ru7|2013-01-01 00:00:00|2013-01-01 00:15:00 is made up of the following three parts:... | # Space\-Time\-Boxes node #
Space\-Time\-Boxes (STB) are an extension of Geohashed spatial locations\. More specifically, an STB is an alphanumeric string that represents a regularly shaped region of space and time\.
For example, the STB dr5ru7\|2013\-01\-01 00:00:00\|2013\-01\-01 00:15:00 is made up of the followin... | <!doctype html>
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<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="Space-Time-Boxes (STB) are an extension of Geohashed spatial locations.... |
909B04011F4C2211D6D945EC82217E3F89A79BD7 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/disable_nodes.html?context=cdpaas&locale=en | Disabling nodes in a flow (SPSS Modeler) | Disabling nodes in a flow
You can disable process nodes that have a single input so that they're ignored when the flow runs. This saves you from having to remove or bypass the node and means you can leave it connected to the remaining nodes.
You can still open and edit the node settings; however, any changes will n... | # Disabling nodes in a flow #
You can disable process nodes that have a single input so that they're ignored when the flow runs\. This saves you from having to remove or bypass the node and means you can leave it connected to the remaining nodes\.
You can still open and edit the node settings; however, any changes wi... | <!doctype html>
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
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338F12B976B522389F5FABE438280565490FB280 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/discriminant.html?context=cdpaas&locale=en | Discriminant node (SPSS Modeler) | Discriminant node
Discriminant analysis builds a predictive model for group membership. The model is composed of a discriminant function (or, for more than two groups, a set of discriminant functions) based on linear combinations of the predictor variables that provide the best discrimination between the groups. The... | # Discriminant node #
Discriminant analysis builds a predictive model for group membership\. The model is composed of a discriminant function (or, for more than two groups, a set of discriminant functions) based on linear combinations of the predictor variables that provide the best discrimination between the groups\.... | <!doctype html>
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<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="Discriminant analysis builds a predictive model for group membership. T... |
5C597F82EC8484220A6FB3193DC78B878E8698F6 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/distinct.html?context=cdpaas&locale=en | Distinct node (SPSS Modeler) | Distinct node
Duplicate records in a data set must be removed before data mining can begin. For example, in a marketing database, individuals may appear multiple times with different address or company information. You can use the Distinct node to find or remove duplicate records in your data, or to create a single,... | # Distinct node #
Duplicate records in a data set must be removed before data mining can begin\. For example, in a marketing database, individuals may appear multiple times with different address or company information\. You can use the Distinct node to find or remove duplicate records in your data, or to create a sin... | <!doctype html>
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<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="Duplicate records in a data set must be removed before data mining can ... |
570AF2AAF268A3DF1D959D54A5BE1790DC43EAD5 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/distribution.html?context=cdpaas&locale=en | Distribution node (SPSS Modeler) | Distribution node
A distribution graph or table shows the occurrence of symbolic (non-numeric) values, such as mortgage type or gender, in a dataset. A typical use of the Distribution node is to show imbalances in the data that you can rectify by using a Balance node before creating a model. You can automatically ge... | # Distribution node #
A distribution graph or table shows the occurrence of symbolic (non\-numeric) values, such as mortgage type or gender, in a dataset\. A typical use of the Distribution node is to show imbalances in the data that you can rectify by using a Balance node before creating a model\. You can automatical... | <!doctype html>
<html lang="en-us">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
<meta charset="UTF-8">
<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="A distribution graph or table shows the occurrence of symbolic (non-num... |
D5D31FDA0EEBFCDD87005ED54EBEDFD164FA073B | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/dvcharts.html?context=cdpaas&locale=en | Charts node (SPSS Modeler) | Charts node
With the Charts node, you can launch the chart builder and create chart definitions to save with your flow. Then when you run the node, chart output is generated.
The Charts node is available under the Graphs section on the node palette. After adding a Charts node to your flow, double-click it to open t... | # Charts node #
With the Charts node, you can launch the chart builder and create chart definitions to save with your flow\. Then when you run the node, chart output is generated\.
The Charts node is available under the Graphs section on the node palette\. After adding a Charts node to your flow, double\-click it to ... | <!doctype html>
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<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="With the Charts node, you can launch the chart builder and create chart... |
8C53BD47030C9BF4E7DBF1EA482CDED9CC8ABAD4 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/ensemble.html?context=cdpaas&locale=en | Ensemble node (SPSS Modeler) | Ensemble node
The Ensemble node combines two or more model nuggets to obtain more accurate predictions than can be gained from any of the individual models. By combining predictions from multiple models, limitations in individual models may be avoided, resulting in a higher overall accuracy. Models combined in this ... | # Ensemble node #
The Ensemble node combines two or more model nuggets to obtain more accurate predictions than can be gained from any of the individual models\. By combining predictions from multiple models, limitations in individual models may be avoided, resulting in a higher overall accuracy\. Models combined in t... | <!doctype html>
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="The Ensemble node combines two or more model nuggets to obtain more acc... |
4F733928B0F749FFDDF2E6DAEF646A0524C54D67 | https://dataplatform.cloud.ibm.com/docs/content/wsd/nodes/evaluation.html?context=cdpaas&locale=en | Evaluation node (SPSS Modeler) | Evaluation node
The Evaluation node offers an easy way to evaluate and compare predictive models to choose the best model for your application. Evaluation charts show how models perform in predicting particular outcomes. They work by sorting records based on the predicted value and confidence of the prediction, spli... | # Evaluation node #
The Evaluation node offers an easy way to evaluate and compare predictive models to choose the best model for your application\. Evaluation charts show how models perform in predicting particular outcomes\. They work by sorting records based on the predicted value and confidence of the prediction, ... | <!doctype html>
<html lang="en-us">
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<meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
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<meta name="dcterms.rights" content="© Copyright IBM Corporation 2023">
<meta name="description" content="The Evaluation node offers an easy way to evaluate and compare predicti... |
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