diff --git "a/Train-Reports/CPP/report_full_UTD057DV.html" "b/Train-Reports/CPP/report_full_UTD057DV.html" new file mode 100644--- /dev/null +++ "b/Train-Reports/CPP/report_full_UTD057DV.html" @@ -0,0 +1,342 @@ + + + + GENE_FAMILY: CPP + + + +
+

GENE_FAMILY: CPP

+
+ +
+
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       1289       50.39
+0       1269       49.61
+

Additional Metrics

+
    +
  • Total Samples: 2558
    • +
  • Imbalance Ratio: 1.02
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9838    0.9590    0.9712       317
+     Class 1     0.9607    0.9845    0.9725       323
+
+    accuracy                         0.9719       640
+   macro avg     0.9723    0.9718    0.9719       640
+weighted avg     0.9722    0.9719    0.9719       640
+
+

Metrics

+
+
    +
  • True Positives (TP): 318
    • +
  • True Negatives (TN): 304
    • +
+
    +
  • False Positives (FP): 13
    • +
  • False Negatives (FN): 5
    • +
+
+
+
+

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       1289       50.39
+0       1269       49.61
+

Additional Metrics

+
    +
  • Total Samples: 2558
    • +
  • Imbalance Ratio: 1.02
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9937    0.9968    0.9953       317
+     Class 1     0.9969    0.9938    0.9953       323
+
+    accuracy                         0.9953       640
+   macro avg     0.9953    0.9953    0.9953       640
+weighted avg     0.9953    0.9953    0.9953       640
+
+

Metrics

+
+
    +
  • True Positives (TP): 321
    • +
  • True Negatives (TN): 316
    • +
+
    +
  • False Positives (FP): 1
    • +
  • False Negatives (FN): 2
    • +
+
+
+
+

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       1289       50.39
+0       1269       49.61
+

Additional Metrics

+
    +
  • Total Samples: 2558
    • +
  • Imbalance Ratio: 1.02
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9814    1.0000    0.9906       317
+     Class 1     1.0000    0.9814    0.9906       323
+
+    accuracy                         0.9906       640
+   macro avg     0.9907    0.9907    0.9906       640
+weighted avg     0.9908    0.9906    0.9906       640
+
+

Metrics

+
+
    +
  • True Positives (TP): 317
    • +
  • True Negatives (TN): 317
    • +
+
    +
  • False Positives (FP): 0
    • +
  • False Negatives (FN): 6
    • +
+
+
+
+

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       1289       50.39
+0       1269       49.61
+

Additional Metrics

+
    +
  • Total Samples: 2558
    • +
  • Imbalance Ratio: 1.02
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9724    1.0000    0.9860       317
+     Class 1     1.0000    0.9721    0.9859       323
+
+    accuracy                         0.9859       640
+   macro avg     0.9862    0.9861    0.9859       640
+weighted avg     0.9863    0.9859    0.9859       640
+
+

Metrics

+
+
    +
  • True Positives (TP): 314
    • +
  • True Negatives (TN): 317
    • +
+
    +
  • False Positives (FP): 0
    • +
  • False Negatives (FN): 9
    • +
+
+
+
+

Confusion Matrix

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