diff --git "a/Train-Reports/FAR1/report_EMT02YIS.html" "b/Train-Reports/FAR1/report_EMT02YIS.html" new file mode 100644--- /dev/null +++ "b/Train-Reports/FAR1/report_EMT02YIS.html" @@ -0,0 +1,265 @@ + + + + GENE_FAMILY: FAR1 + + + +
+

GENE_FAMILY: FAR1

+
+ +
+
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       2505        50.1
+0       2495        49.9
+

Additional Metrics

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

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9775    0.9559    0.9666       499
+     Class 1     0.9570    0.9780    0.9674       501
+
+    accuracy                         0.9670      1000
+   macro avg     0.9672    0.9670    0.9670      1000
+weighted avg     0.9672    0.9670    0.9670      1000
+
+

Metrics

+
+
    +
  • True Positives (TP): 490
    • +
  • True Negatives (TN): 477
    • +
+
    +
  • False Positives (FP): 22
    • +
  • False Negatives (FN): 11
    • +
+
+
+
+

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       2505        50.1
+0       2495        49.9
+

Additional Metrics

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

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9960    0.9860    0.9909       499
+     Class 1     0.9862    0.9960    0.9911       501
+
+    accuracy                         0.9910      1000
+   macro avg     0.9911    0.9910    0.9910      1000
+weighted avg     0.9910    0.9910    0.9910      1000
+
+

Metrics

+
+
    +
  • True Positives (TP): 499
    • +
  • True Negatives (TN): 492
    • +
+
    +
  • False Positives (FP): 7
    • +
  • 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)                 │      37,925,888 │
+├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
+│ 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: 113,901,317 (434.50 MB)
+ Trainable params: 37,967,105 (144.83 MB)
+ Non-trainable params: 0 (0.00 B)
+ Optimizer params: 75,934,212 (289.67 MB)
+
+
+
+

Learning Curve

+ Learning Curve +
+
+
+
+

Class Distribution

+ 
       Count  Percentage
+class                   
+1       2505        50.1
+0       2495        49.9
+

Additional Metrics

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

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9822    0.9960    0.9891       499
+     Class 1     0.9960    0.9820    0.9889       501
+
+    accuracy                         0.9890      1000
+   macro avg     0.9891    0.9890    0.9890      1000
+weighted avg     0.9891    0.9890    0.9890      1000
+
+

Metrics

+
+
    +
  • True Positives (TP): 492
    • +
  • True Negatives (TN): 497
    • +
+
    +
  • False Positives (FP): 2
    • +
  • False Negatives (FN): 9
    • +
+
+
+
+

Confusion Matrix

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