diff --git "a/Train-Reports/NAC/report_8TPAERZI.html" "b/Train-Reports/NAC/report_8TPAERZI.html" new file mode 100644--- /dev/null +++ "b/Train-Reports/NAC/report_8TPAERZI.html" @@ -0,0 +1,265 @@ + + + + GENE_FAMILY: NAC + + + +
+

GENE_FAMILY: NAC

+
+ +
+
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     0.9606    0.9740    0.9672       500
+     Class 1     0.9736    0.9600    0.9668       500
+
+    accuracy                         0.9670      1000
+   macro avg     0.9671    0.9670    0.9670      1000
+weighted avg     0.9671    0.9670    0.9670      1000
+
+

Metrics

+
+
    +
  • True Positives (TP): 480
    • +
  • True Negatives (TN): 487
    • +
+
    +
  • False Positives (FP): 13
    • +
  • False Negatives (FN): 20
    • +
+
+
+
+

Confusion Matrix

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

Model Architecture

+ 
Model: "FEEDFORWARD_k3"
+┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
+┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
+│ dense_5 (Dense)                      │ (None, 256)                 │       2,241,536 │
+├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
+│ 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: 6,854,405 (26.15 MB)
+ Trainable params: 2,284,801 (8.72 MB)
+ Non-trainable params: 0 (0.00 B)
+ Optimizer params: 4,569,604 (17.43 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     0.9880    0.9920    0.9900       500
+     Class 1     0.9920    0.9880    0.9900       500
+
+    accuracy                         0.9900      1000
+   macro avg     0.9900    0.9900    0.9900      1000
+weighted avg     0.9900    0.9900    0.9900      1000
+
+

Metrics

+
+
    +
  • True Positives (TP): 494
    • +
  • True Negatives (TN): 496
    • +
+
    +
  • False Positives (FP): 4
    • +
  • False Negatives (FN): 6
    • +
+
+
+
+

Confusion Matrix

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

Model Architecture

+ 
Model: "FEEDFORWARD_k4"
+┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
+┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
+│ dense_10 (Dense)                     │ (None, 256)                 │      37,458,176 │
+├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
+│ 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: 112,498,181 (429.15 MB)
+ Trainable params: 37,499,393 (143.05 MB)
+ Non-trainable params: 0 (0.00 B)
+ Optimizer params: 74,998,788 (286.10 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     0.9747    1.0000    0.9872       500
+     Class 1     1.0000    0.9740    0.9868       500
+
+    accuracy                         0.9870      1000
+   macro avg     0.9873    0.9870    0.9870      1000
+weighted avg     0.9873    0.9870    0.9870      1000
+
+

Metrics

+
+
    +
  • True Positives (TP): 487
    • +
  • True Negatives (TN): 500
    • +
+
    +
  • False Positives (FP): 0
    • +
  • False Negatives (FN): 13
    • +
+
+
+
+

Confusion Matrix

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