diff --git "a/Train-Reports/AP2/report_full_BO1ID6QX.html" "b/Train-Reports/AP2/report_full_BO1ID6QX.html" new file mode 100644--- /dev/null +++ "b/Train-Reports/AP2/report_full_BO1ID6QX.html" @@ -0,0 +1,342 @@ + + + + GENE_FAMILY: AP2 + + + +
+

GENE_FAMILY: AP2

+
+ +
+
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       3569       50.16
+0       3546       49.84
+

Additional Metrics

+
    +
  • Total Samples: 7115
    • +
  • Imbalance Ratio: 1.01
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9739    0.9684    0.9712       887
+     Class 1     0.9688    0.9742    0.9715       892
+
+    accuracy                         0.9713      1779
+   macro avg     0.9714    0.9713    0.9713      1779
+weighted avg     0.9713    0.9713    0.9713      1779
+
+

Metrics

+
+
    +
  • True Positives (TP): 869
    • +
  • True Negatives (TN): 859
    • +
+
    +
  • False Positives (FP): 28
    • +
  • False Negatives (FN): 23
    • +
+
+
+
+

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       3569       50.16
+0       3546       49.84
+

Additional Metrics

+
    +
  • Total Samples: 7115
    • +
  • Imbalance Ratio: 1.01
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9761    0.9684    0.9723       887
+     Class 1     0.9689    0.9765    0.9726       892
+
+    accuracy                         0.9725      1779
+   macro avg     0.9725    0.9724    0.9725      1779
+weighted avg     0.9725    0.9725    0.9725      1779
+
+

Metrics

+
+
    +
  • True Positives (TP): 871
    • +
  • True Negatives (TN): 859
    • +
+
    +
  • False Positives (FP): 28
    • +
  • False Negatives (FN): 21
    • +
+
+
+
+

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       3569       50.16
+0       3546       49.84
+

Additional Metrics

+
    +
  • Total Samples: 7115
    • +
  • Imbalance Ratio: 1.01
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9629    0.9944    0.9784       887
+     Class 1     0.9942    0.9619    0.9778       892
+
+    accuracy                         0.9781      1779
+   macro avg     0.9785    0.9781    0.9781      1779
+weighted avg     0.9786    0.9781    0.9781      1779
+
+

Metrics

+
+
    +
  • True Positives (TP): 858
    • +
  • True Negatives (TN): 882
    • +
+
    +
  • False Positives (FP): 5
    • +
  • False Negatives (FN): 34
    • +
+
+
+
+

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       3569       50.16
+0       3546       49.84
+

Additional Metrics

+
    +
  • Total Samples: 7115
    • +
  • Imbalance Ratio: 1.01
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9582    0.9831    0.9705       887
+     Class 1     0.9827    0.9574    0.9699       892
+
+    accuracy                         0.9702      1779
+   macro avg     0.9705    0.9702    0.9702      1779
+weighted avg     0.9705    0.9702    0.9702      1779
+
+

Metrics

+
+
    +
  • True Positives (TP): 854
    • +
  • True Negatives (TN): 872
    • +
+
    +
  • False Positives (FP): 15
    • +
  • False Negatives (FN): 38
    • +
+
+
+
+

Confusion Matrix

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