erisdataworks/matematika301

📊 Mathematical Feature Engineering Dataset

This repository provides a synthetic dataset with 200+ rows, created for testing, learning, and experimenting with feature engineering, mathematical transformations, and machine learning pipelines.

📂 Dataset Overview

Each row contains 6 initial variables (x1 … x6) and multiple derived features generated through arithmetic, trigonometric, logarithmic, exponential, statistical, and geometric operations.

Columns Description

• Base Features

  • x1 … x6 → Random continuous variables

• Basic Arithmetic

  • addition → x1 + x2
  • subtraction → x1 - x2
  • multiplication → x1 × x2
  • division → x1 ÷ x2

• Trigonometric

  • sin_x1, cos_x1, tan_x1

• Logarithmic & Roots

  • log_x3 → natural log of x3
  • sqrt_x3 → square root of x3

• Polynomial & Exponential

  • quadratic → quadratic transformation of x1
  • exp_x4 → exponential of x4

• Geometric

  • circle_area → π × (x1)²
  • rectangle_area → x1 × x2
  • triangle_area → 0.5 × x1 × x2

• Statistical

  • mean → average of selected features
  • std_dev → standard deviation
  • hypotenuse → √(x1² + x2²)
  • dot_product → dot product of vectors
  • vector_magnitude → magnitude of vector [x1 … x6]

• Advanced / Engineered

  • complex_operation → custom nonlinear combination
  • x1_scaled … x6_scaled → normalized values
  • x1_squared, x2_squared → polynomial features
  • x1_x2_interaction → interaction between x1 and x2

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🎯 Use Cases

• Practicing feature engineering
• Machine learning model experimentation
• Data transformation testing
• Educational material for:
  • Linear algebra
  • Trigonometry
  • Statistics
  • Geometry

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📜 License

This dataset is open source under the Apache 2.0 License.

Note: This dataset was developed and released by Eris Dataworks, a part of Berinspa.

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