GENE_FAMILY: E2F/DP

MODEL: FEEDFORWARD_k2

Model Architecture

Model: "FEEDFORWARD_k2"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ dense (Dense)                   │ (None, 256)            │        51,456 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ 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: 284,165 (1.08 MB)
 Trainable params: 94,721 (370.00 KB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 189,444 (740.02 KB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1       1424       50.34
0       1405       49.66

Additional Metrics

  • Total Samples: 2829
  • Imbalance Ratio: 1.01

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9913    0.9687    0.9798       351
     Class 1     0.9699    0.9916    0.9806       357

    accuracy                         0.9802       708
   macro avg     0.9806    0.9801    0.9802       708
weighted avg     0.9805    0.9802    0.9802       708

Metrics

  • True Positives (TP): 354
  • True Negatives (TN): 340
  • False Positives (FP): 11
  • False Negatives (FN): 3

Confusion Matrix

Confusion Matrix
MODEL: FEEDFORWARD_k3

Model Architecture

Model: "FEEDFORWARD_k3"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ dense_5 (Dense)                 │ (None, 256)            │       256,256 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ 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: 898,565 (3.43 MB)
 Trainable params: 299,521 (1.14 MB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 599,044 (2.29 MB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1       1424       50.34
0       1405       49.66

Additional Metrics

  • Total Samples: 2829
  • Imbalance Ratio: 1.01

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9915    0.9915    0.9915       351
     Class 1     0.9916    0.9916    0.9916       357

    accuracy                         0.9915       708
   macro avg     0.9915    0.9915    0.9915       708
weighted avg     0.9915    0.9915    0.9915       708

Metrics

  • True Positives (TP): 354
  • True Negatives (TN): 348
  • False Positives (FP): 3
  • False Negatives (FN): 3

Confusion Matrix

Confusion Matrix
MODEL: FEEDFORWARD_k4

Model Architecture

Model: "FEEDFORWARD_k4"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ dense_10 (Dense)                │ (None, 256)            │       256,256 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ 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: 892,421 (3.40 MB)
 Trainable params: 297,473 (1.13 MB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 594,948 (2.27 MB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1       1424       50.34
0       1405       49.66

Additional Metrics

  • Total Samples: 2829
  • Imbalance Ratio: 1.01

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9887    1.0000    0.9943       351
     Class 1     1.0000    0.9888    0.9944       357

    accuracy                         0.9944       708
   macro avg     0.9944    0.9944    0.9944       708
weighted avg     0.9944    0.9944    0.9944       708

Metrics

  • True Positives (TP): 353
  • True Negatives (TN): 351
  • False Positives (FP): 0
  • False Negatives (FN): 4

Confusion Matrix

Confusion Matrix
MODEL: FEEDFORWARD_k5

Model Architecture

Model: "FEEDFORWARD_k5"
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓
┃ Layer (type)                    ┃ Output Shape           ┃       Param # ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩
│ dense_14 (Dense)                │ (None, 512)            │       512,512 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ dropout_11 (Dropout)            │ (None, 512)            │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ dense_15 (Dense)                │ (None, 128)            │        65,664 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ dropout_12 (Dropout)            │ (None, 128)            │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ dense_16 (Dense)                │ (None, 64)             │         8,256 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ dropout_13 (Dropout)            │ (None, 64)             │             0 │
├─────────────────────────────────┼────────────────────────┼───────────────┤
│ dense_17 (Dense)                │ (None, 1)              │            65 │
└─────────────────────────────────┴────────────────────────┴───────────────┘
 Total params: 1,759,493 (6.71 MB)
 Trainable params: 586,497 (2.24 MB)
 Non-trainable params: 0 (0.00 B)
 Optimizer params: 1,172,996 (4.47 MB)

Learning Curve

Learning Curve

Class Distribution

       Count  Percentage
class                   
1       1424       50.34
0       1405       49.66

Additional Metrics

  • Total Samples: 2829
  • Imbalance Ratio: 1.01

Classification Report

              precision    recall  f1-score   support

     Class 0     0.9887    1.0000    0.9943       351
     Class 1     1.0000    0.9888    0.9944       357

    accuracy                         0.9944       708
   macro avg     0.9944    0.9944    0.9944       708
weighted avg     0.9944    0.9944    0.9944       708

Metrics

  • True Positives (TP): 353
  • True Negatives (TN): 351
  • False Positives (FP): 0
  • False Negatives (FN): 4

Confusion Matrix

Confusion Matrix