GENE_FAMILY: SAP

MODEL: FEEDFORWARD_k2

Model Architecture

Model: "FEEDFORWARD_k2"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ dense (Dense)                        │ (None, 256)                 │         112,128 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ 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: 466,181 (1.78 MB)
 Trainable params: 155,393 (607.00 KB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 310,788 (1.19 MB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1        164       50.77
0        159       49.23

Additional Metrics

  • Total Samples: 323
  • Imbalance Ratio: 1.03

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9697    1.0000    0.9846        32
     Class 1     1.0000    0.9697    0.9846        33

    accuracy                         0.9846        65
   macro avg     0.9848    0.9848    0.9846        65
weighted avg     0.9851    0.9846    0.9846        65

Metrics

  • True Positives (TP): 32
  • True Negatives (TN): 32
  • False Positives (FP): 0
  • False Negatives (FN): 1

Confusion Matrix

Confusion Matrix
MODEL: FEEDFORWARD_k3

Model Architecture

Model: "FEEDFORWARD_k3"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ dense_5 (Dense)                      │ (None, 256)                 │       2,011,392 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ 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: 6,163,973 (23.51 MB)
 Trainable params: 2,054,657 (7.84 MB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 4,109,316 (15.68 MB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1        164       50.77
0        159       49.23

Additional Metrics

  • Total Samples: 323
  • Imbalance Ratio: 1.03

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9697    1.0000    0.9846        32
     Class 1     1.0000    0.9697    0.9846        33

    accuracy                         0.9846        65
   macro avg     0.9848    0.9848    0.9846        65
weighted avg     0.9851    0.9846    0.9846        65

Metrics

  • True Positives (TP): 32
  • True Negatives (TN): 32
  • False Positives (FP): 0
  • False Negatives (FN): 1

Confusion Matrix

Confusion Matrix
MODEL: FEEDFORWARD_k4

Model Architecture

Model: "FEEDFORWARD_k4"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ dense_10 (Dense)                     │ (None, 256)                 │      13,513,728 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ 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: 40,664,837 (155.12 MB)
 Trainable params: 13,554,945 (51.71 MB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 27,109,892 (103.42 MB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1        164       50.77
0        159       49.23

Additional Metrics

  • Total Samples: 323
  • Imbalance Ratio: 1.03

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9697    1.0000    0.9846        32
     Class 1     1.0000    0.9697    0.9846        33

    accuracy                         0.9846        65
   macro avg     0.9848    0.9848    0.9846        65
weighted avg     0.9851    0.9846    0.9846        65

Metrics

  • True Positives (TP): 32
  • True Negatives (TN): 32
  • False Positives (FP): 0
  • False Negatives (FN): 1

Confusion Matrix

Confusion Matrix