GENE_FAMILY: CPP

MODEL: FEEDFORWARD_k2

Model Architecture

Model: "FEEDFORWARD_k2"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ dense (Dense)                        │ (None, 256)                 │         113,152 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout (Dropout)                    │ (None, 256)                 │               0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_1 (Dense)                      │ (None, 128)                 │          32,896 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_1 (Dropout)                  │ (None, 128)                 │               0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_2 (Dense)                      │ (None, 64)                  │           8,256 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_2 (Dropout)                  │ (None, 64)                  │               0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_3 (Dense)                      │ (None, 32)                  │           2,080 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_3 (Dropout)                  │ (None, 32)                  │               0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_4 (Dense)                      │ (None, 1)                   │              33 │
└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘
 Total params: 469,253 (1.79 MB)
 Trainable params: 156,417 (611.00 KB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 312,836 (1.19 MB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1       1612       50.41
0       1586       49.59

Additional Metrics

  • Total Samples: 3198
  • Imbalance Ratio: 1.02

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9873    0.9842    0.9858       317
     Class 1     0.9846    0.9876    0.9861       323

    accuracy                         0.9859       640
   macro avg     0.9860    0.9859    0.9859       640
weighted avg     0.9859    0.9859    0.9859       640

Metrics

  • True Positives (TP): 319
  • True Negatives (TN): 312
  • False Positives (FP): 5
  • False Negatives (FN): 4

Confusion Matrix

Confusion Matrix
MODEL: FEEDFORWARD_k3

Model Architecture

Model: "FEEDFORWARD_k3"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ dense_5 (Dense)                      │ (None, 256)                 │       2,211,840 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_4 (Dropout)                  │ (None, 256)                 │               0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_6 (Dense)                      │ (None, 128)                 │          32,896 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_5 (Dropout)                  │ (None, 128)                 │               0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_7 (Dense)                      │ (None, 64)                  │           8,256 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_6 (Dropout)                  │ (None, 64)                  │               0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_8 (Dense)                      │ (None, 32)                  │           2,080 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_7 (Dropout)                  │ (None, 32)                  │               0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_9 (Dense)                      │ (None, 1)                   │              33 │
└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘
 Total params: 6,765,317 (25.81 MB)
 Trainable params: 2,255,105 (8.60 MB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 4,510,212 (17.21 MB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1       1612       50.41
0       1586       49.59

Additional Metrics

  • Total Samples: 3198
  • Imbalance Ratio: 1.02

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9814    1.0000    0.9906       317
     Class 1     1.0000    0.9814    0.9906       323

    accuracy                         0.9906       640
   macro avg     0.9907    0.9907    0.9906       640
weighted avg     0.9908    0.9906    0.9906       640

Metrics

  • True Positives (TP): 317
  • True Negatives (TN): 317
  • False Positives (FP): 0
  • False Negatives (FN): 6

Confusion Matrix

Confusion Matrix
MODEL: FEEDFORWARD_k4

Model Architecture

Model: "FEEDFORWARD_k4"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ dense_10 (Dense)                     │ (None, 256)                 │      34,098,176 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_8 (Dropout)                  │ (None, 256)                 │               0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_11 (Dense)                     │ (None, 128)                 │          32,896 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_9 (Dropout)                  │ (None, 128)                 │               0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_12 (Dense)                     │ (None, 64)                  │           8,256 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dropout_10 (Dropout)                 │ (None, 64)                  │               0 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ dense_13 (Dense)                     │ (None, 1)                   │              65 │
└──────────────────────────────────────┴─────────────────────────────┴─────────────────┘
 Total params: 102,418,181 (390.69 MB)
 Trainable params: 34,139,393 (130.23 MB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 68,278,788 (260.46 MB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1       1612       50.41
0       1586       49.59

Additional Metrics

  • Total Samples: 3198
  • Imbalance Ratio: 1.02

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9754    1.0000    0.9875       317
     Class 1     1.0000    0.9752    0.9875       323

    accuracy                         0.9875       640
   macro avg     0.9877    0.9876    0.9875       640
weighted avg     0.9878    0.9875    0.9875       640

Metrics

  • True Positives (TP): 315
  • True Negatives (TN): 317
  • False Positives (FP): 0
  • False Negatives (FN): 8

Confusion Matrix

Confusion Matrix