diff --git "a/Train-Reports/C2H2/report_W98H8M3J.html" "b/Train-Reports/C2H2/report_W98H8M3J.html" new file mode 100644--- /dev/null +++ "b/Train-Reports/C2H2/report_W98H8M3J.html" @@ -0,0 +1,265 @@ + + + + GENE_FAMILY: C2H2 + + + +
+

GENE_FAMILY: C2H2

+
+ +
+
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       2502       50.04
+0       2498       49.96
+

Additional Metrics

+
    +
  • Total Samples: 5000
  • +
  • Imbalance Ratio: 1.00
  • +
+
+
+

Classification Report

+
              precision    recall  f1-score   support
+
+     Class 0     0.9552    0.9380    0.9465       500
+     Class 1     0.9391    0.9560    0.9475       500
+
+    accuracy                         0.9470      1000
+   macro avg     0.9471    0.9470    0.9470      1000
+weighted avg     0.9471    0.9470    0.9470      1000
+
+

Metrics

+
+
    +
  • True Positives (TP): 478
  • +
  • True Negatives (TN): 469
  • +
+
    +
  • False Positives (FP): 31
  • +
  • False Negatives (FN): 22
  • +
+
+
+
+

Confusion Matrix

+ Confusion Matrix +
+
+
+ +
+
MODEL: FEEDFORWARD_k3
+
+
+

Model Architecture

+
Model: "FEEDFORWARD_k3"
+┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
+┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
+│ dense_5 (Dense)                      │ (None, 256)                 │       2,219,008 │
+├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
+│ 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: 6,786,821 (25.89 MB)
+ Trainable params: 2,262,273 (8.63 MB)
+ Non-trainable params: 0 (0.00 B)
+ Optimizer params: 4,524,548 (17.26 MB)
+
+
+
+

Learning Curve

+ Learning Curve +
+
+
+
+

Class Distribution

+
       Count  Percentage
+class                   
+1       2502       50.04
+0       2498       49.96
+

Additional Metrics

+
    +
  • Total Samples: 5000
  • +
  • Imbalance Ratio: 1.00
  • +
+
+
+

Classification Report

+
              precision    recall  f1-score   support
+
+     Class 0     0.9612    0.9920    0.9764       500
+     Class 1     0.9917    0.9600    0.9756       500
+
+    accuracy                         0.9760      1000
+   macro avg     0.9765    0.9760    0.9760      1000
+weighted avg     0.9765    0.9760    0.9760      1000
+
+

Metrics

+
+
    +
  • True Positives (TP): 480
  • +
  • True Negatives (TN): 496
  • +
+
    +
  • False Positives (FP): 4
  • +
  • False Negatives (FN): 20
  • +
+
+
+
+

Confusion Matrix

+ Confusion Matrix +
+
+
+ +
+
MODEL: FEEDFORWARD_k4
+
+
+

Model Architecture

+
Model: "FEEDFORWARD_k4"
+┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
+┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
+│ dense_10 (Dense)                     │ (None, 256)                 │      36,928,000 │
+├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
+│ 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: 110,907,653 (423.08 MB)
+ Trainable params: 36,969,217 (141.03 MB)
+ Non-trainable params: 0 (0.00 B)
+ Optimizer params: 73,938,436 (282.05 MB)
+
+
+
+

Learning Curve

+ Learning Curve +
+
+
+
+

Class Distribution

+
       Count  Percentage
+class                   
+1       2502       50.04
+0       2498       49.96
+

Additional Metrics

+
    +
  • Total Samples: 5000
  • +
  • Imbalance Ratio: 1.00
  • +
+
+
+

Classification Report

+
              precision    recall  f1-score   support
+
+     Class 0     0.9634    1.0000    0.9814       500
+     Class 1     1.0000    0.9620    0.9806       500
+
+    accuracy                         0.9810      1000
+   macro avg     0.9817    0.9810    0.9810      1000
+weighted avg     0.9817    0.9810    0.9810      1000
+
+

Metrics

+
+
    +
  • True Positives (TP): 481
  • +
  • True Negatives (TN): 500
  • +
+
    +
  • False Positives (FP): 0
  • +
  • False Negatives (FN): 19
  • +
+
+
+
+

Confusion Matrix

+ Confusion Matrix +
+
+
+ + + + \ No newline at end of file