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  1. .gitattributes +10 -0
  2. DenseNet169/BINARY_DenseNet169_Round1/.ipynb_checkpoints/confusion_matrix-checkpoint.png +0 -0
  3. DenseNet169/BINARY_DenseNet169_Round1/BINARY_DenseNet169_Round1.keras +3 -0
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  11. DenseNet169/BINARY_DenseNet169_Round2/BINARY_DenseNet169_Round2.keras +3 -0
  12. DenseNet169/BINARY_DenseNet169_Round2/classification_metrics.txt +12 -0
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  14. DenseNet169/BINARY_DenseNet169_Round2/roc_curve.png +0 -0
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  18. DenseNet169/BINARY_DenseNet169_Round2/training_validation_metrics.txt +182 -0
  19. DenseNet169/BINARY_DenseNet169_Round3/.ipynb_checkpoints/confusion_matrix-checkpoint.png +0 -0
  20. DenseNet169/BINARY_DenseNet169_Round3/BINARY_DenseNet169_Round3.keras +3 -0
  21. DenseNet169/BINARY_DenseNet169_Round3/classification_metrics.txt +12 -0
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  27. DenseNet169/BINARY_DenseNet169_Round3/training_validation_metrics.txt +182 -0
  28. DenseNet169/BINARY_DenseNet169_Round4/BINARY_DenseNet169_Round4.keras +3 -0
  29. DenseNet169/BINARY_DenseNet169_Round4/classification_metrics.txt +12 -0
  30. DenseNet169/BINARY_DenseNet169_Round4/confusion_matrix.png +0 -0
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  32. DenseNet169/BINARY_DenseNet169_Round4/testing_metrics.txt +3 -0
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  35. DenseNet169/BINARY_DenseNet169_Round4/training_validation_metrics.txt +182 -0
  36. DenseNet169/BINARY_DenseNet169_Round5/BINARY_DenseNet169_Round5.keras +3 -0
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  43. DenseNet169/BINARY_DenseNet169_Round5/training_validation_metrics.txt +182 -0
  44. MobileNetV2/BINARY_MobileNetV2_Round1/.ipynb_checkpoints/confusion_matrix-checkpoint.png +0 -0
  45. MobileNetV2/BINARY_MobileNetV2_Round1/BINARY_MobileNetV2_Round1.keras +3 -0
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+ Training and Validation Metrics Per Epoch
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+ Training and Validation Metrics Per Epoch
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+ --------------------------------------------------
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+ Validation Accuracy: 0.9998
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+ Training Loss: 0.0003
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+ Validation Loss: 0.0004
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+ --------------------------------------------------
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+ Epoch 27
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+ Training Accuracy: 1.0000
161
+ Validation Accuracy: 1.0000
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+ Training Loss: 0.0001
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+ Validation Loss: 0.0002
164
+ --------------------------------------------------
165
+ Epoch 28
166
+ Training Accuracy: 0.9999
167
+ Validation Accuracy: 0.9998
168
+ Training Loss: 0.0001
169
+ Validation Loss: 0.0002
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+ --------------------------------------------------
171
+ Epoch 29
172
+ Training Accuracy: 0.9999
173
+ Validation Accuracy: 0.9998
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+ Training Loss: 0.0002
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+ Validation Loss: 0.0005
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+ --------------------------------------------------
177
+ Epoch 30
178
+ Training Accuracy: 1.0000
179
+ Validation Accuracy: 0.9998
180
+ Training Loss: 0.0001
181
+ Validation Loss: 0.0002
182
+ --------------------------------------------------
MobileNetV2/BINARY_MobileNetV2_Round1/.ipynb_checkpoints/confusion_matrix-checkpoint.png ADDED
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+ Precision: 0.9984
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+ Recall: 0.9992
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+ Sensitivity: 0.9992
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+ Specificity: 0.9984
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+ F1-Score: 0.9988
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+ AUC: 1.0000
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+ MCC: 0.9976
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+ Cohen's Kappa: 0.9976
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+ Balanced Accuracy: 0.9988
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+ Jaccard Index: 0.9976
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+ Log Loss: 0.0034
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+ F0.5-Score: 0.9986
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+ accuracy: 0.9988
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+ auc: 1.0000
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+ loss: 0.0034
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