diff --git "a/Train-Reports/DBB/report_MI8VTH3N.html" "b/Train-Reports/DBB/report_MI8VTH3N.html" new file mode 100644--- /dev/null +++ "b/Train-Reports/DBB/report_MI8VTH3N.html" @@ -0,0 +1,265 @@ + + + + GENE_FAMILY: DBB + + + +
+

GENE_FAMILY: DBB

+
+ +
+
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       1651        50.4
+0       1625        49.6
+

Additional Metrics

+
    +
  • Total Samples: 3276
    • +
  • Imbalance Ratio: 1.02
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9969    0.9815    0.9891       325
+     Class 1     0.9821    0.9970    0.9895       331
+
+    accuracy                         0.9893       656
+   macro avg     0.9895    0.9893    0.9893       656
+weighted avg     0.9894    0.9893    0.9893       656
+
+

Metrics

+
+
    +
  • True Positives (TP): 330
    • +
  • True Negatives (TN): 319
    • +
+
    +
  • False Positives (FP): 6
    • +
  • 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)                 │       2,198,016 │
+├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
+│ 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: 6,723,845 (25.65 MB)
+ Trainable params: 2,241,281 (8.55 MB)
+ Non-trainable params: 0 (0.00 B)
+ Optimizer params: 4,482,564 (17.10 MB)
+
+
+
+

Learning Curve

+ Learning Curve +
+
+
+
+

Class Distribution

+ 
       Count  Percentage
+class                   
+1       1651        50.4
+0       1625        49.6
+

Additional Metrics

+
    +
  • Total Samples: 3276
    • +
  • Imbalance Ratio: 1.02
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9969    0.9908    0.9938       325
+     Class 1     0.9910    0.9970    0.9940       331
+
+    accuracy                         0.9939       656
+   macro avg     0.9939    0.9939    0.9939       656
+weighted avg     0.9939    0.9939    0.9939       656
+
+

Metrics

+
+
    +
  • True Positives (TP): 330
    • +
  • True Negatives (TN): 322
    • +
+
    +
  • False Positives (FP): 3
    • +
  • 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)                 │      33,022,720 │
+├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
+│ 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: 99,191,813 (378.39 MB)
+ Trainable params: 33,063,937 (126.13 MB)
+ Non-trainable params: 0 (0.00 B)
+ Optimizer params: 66,127,876 (252.26 MB)
+
+
+
+

Learning Curve

+ Learning Curve +
+
+
+
+

Class Distribution

+ 
       Count  Percentage
+class                   
+1       1651        50.4
+0       1625        49.6
+

Additional Metrics

+
    +
  • Total Samples: 3276
    • +
  • Imbalance Ratio: 1.02
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9817    0.9908    0.9862       325
+     Class 1     0.9909    0.9819    0.9863       331
+
+    accuracy                         0.9863       656
+   macro avg     0.9863    0.9863    0.9863       656
+weighted avg     0.9863    0.9863    0.9863       656
+
+

Metrics

+
+
    +
  • True Positives (TP): 325
    • +
  • True Negatives (TN): 322
    • +
+
    +
  • False Positives (FP): 3
    • +
  • False Negatives (FN): 6
    • +
+
+
+
+

Confusion Matrix

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