GENE_FAMILY: HB-PHD

MODEL: FEEDFORWARD_k2

Model Architecture

Model: "FEEDFORWARD_k2"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ dense (Dense)                        │ (None, 256)                 │         111,872 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ 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: 465,413 (1.78 MB)
 Trainable params: 155,137 (606.00 KB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 310,276 (1.18 MB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1        477       51.18
0        455       48.82

Additional Metrics

  • Total Samples: 932
  • Imbalance Ratio: 1.05

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9891    1.0000    0.9945        91
     Class 1     1.0000    0.9896    0.9948        96

    accuracy                         0.9947       187
   macro avg     0.9946    0.9948    0.9946       187
weighted avg     0.9947    0.9947    0.9947       187

Metrics

  • True Positives (TP): 95
  • True Negatives (TN): 91
  • 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)                 │       2,097,920 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ 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: 6,423,557 (24.50 MB)
 Trainable params: 2,141,185 (8.17 MB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 4,282,372 (16.34 MB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1        477       51.18
0        455       48.82

Additional Metrics

  • Total Samples: 932
  • Imbalance Ratio: 1.05

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9891    1.0000    0.9945        91
     Class 1     1.0000    0.9896    0.9948        96

    accuracy                         0.9947       187
   macro avg     0.9946    0.9948    0.9946       187
weighted avg     0.9947    0.9947    0.9947       187

Metrics

  • True Positives (TP): 95
  • True Negatives (TN): 91
  • 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)                 │      24,038,656 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ 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: 72,239,621 (275.57 MB)
 Trainable params: 24,079,873 (91.86 MB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 48,159,748 (183.71 MB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1        477       51.18
0        455       48.82

Additional Metrics

  • Total Samples: 932
  • Imbalance Ratio: 1.05

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9785    1.0000    0.9891        91
     Class 1     1.0000    0.9792    0.9895        96

    accuracy                         0.9893       187
   macro avg     0.9892    0.9896    0.9893       187
weighted avg     0.9895    0.9893    0.9893       187

Metrics

  • True Positives (TP): 94
  • True Negatives (TN): 91
  • False Positives (FP): 0
  • False Negatives (FN): 2

Confusion Matrix

Confusion Matrix