diff --git "a/Train-Reports/LFY/report_6EYA898R.html" "b/Train-Reports/LFY/report_6EYA898R.html" new file mode 100644--- /dev/null +++ "b/Train-Reports/LFY/report_6EYA898R.html" @@ -0,0 +1,265 @@ + + + + GENE_FAMILY: LFY + + + +
+

GENE_FAMILY: LFY

+
+ +
+
MODEL: FEEDFORWARD_k2
+
+
+

Model Architecture

+ 
Model: "FEEDFORWARD_k2"
+┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
+┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
+│ dense (Dense)                        │ (None, 256)                 │         111,360 │
+├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
+│ 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: 463,877 (1.77 MB)
+ Trainable params: 154,625 (604.00 KB)
+ Non-trainable params: 0 (0.00 B)
+ Optimizer params: 309,252 (1.18 MB)
+
+
+
+

Learning Curve

+ Learning Curve +
+
+
+
+

Class Distribution

+ 
       Count  Percentage
+class                   
+1        253       51.53
+0        238       48.47
+

Additional Metrics

+
    +
  • Total Samples: 491
    • +
  • Imbalance Ratio: 1.06
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     1.0000    0.9792    0.9895        48
+     Class 1     0.9808    1.0000    0.9903        51
+
+    accuracy                         0.9899        99
+   macro avg     0.9904    0.9896    0.9899        99
+weighted avg     0.9901    0.9899    0.9899        99
+
+

Metrics

+
+
    +
  • True Positives (TP): 51
    • +
  • True Negatives (TN): 47
    • +
+
    +
  • False Positives (FP): 1
    • +
  • False Negatives (FN): 0
    • +
+
+
+
+

Confusion Matrix

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

Model Architecture

+ 
Model: "FEEDFORWARD_k3"
+┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
+┃ Layer (type)                         ┃ Output Shape                ┃         Param # ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
+│ dense_5 (Dense)                      │ (None, 256)                 │       2,036,736 │
+├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
+│ 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: 6,240,005 (23.80 MB)
+ Trainable params: 2,080,001 (7.93 MB)
+ Non-trainable params: 0 (0.00 B)
+ Optimizer params: 4,160,004 (15.87 MB)
+
+
+
+

Learning Curve

+ Learning Curve +
+
+
+
+

Class Distribution

+ 
       Count  Percentage
+class                   
+1        253       51.53
+0        238       48.47
+

Additional Metrics

+
    +
  • Total Samples: 491
    • +
  • Imbalance Ratio: 1.06
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9796    1.0000    0.9897        48
+     Class 1     1.0000    0.9804    0.9901        51
+
+    accuracy                         0.9899        99
+   macro avg     0.9898    0.9902    0.9899        99
+weighted avg     0.9901    0.9899    0.9899        99
+
+

Metrics

+
+
    +
  • True Positives (TP): 50
    • +
  • True Negatives (TN): 48
    • +
+
    +
  • False Positives (FP): 0
    • +
  • 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)                 │      15,738,112 │
+├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
+│ 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: 47,337,989 (180.58 MB)
+ Trainable params: 15,779,329 (60.19 MB)
+ Non-trainable params: 0 (0.00 B)
+ Optimizer params: 31,558,660 (120.39 MB)
+
+
+
+

Learning Curve

+ Learning Curve +
+
+
+
+

Class Distribution

+ 
       Count  Percentage
+class                   
+1        253       51.53
+0        238       48.47
+

Additional Metrics

+
    +
  • Total Samples: 491
    • +
  • Imbalance Ratio: 1.06
    • +
+
+
+

Classification Report

+ 
              precision    recall  f1-score   support
+
+     Class 0     0.9796    1.0000    0.9897        48
+     Class 1     1.0000    0.9804    0.9901        51
+
+    accuracy                         0.9899        99
+   macro avg     0.9898    0.9902    0.9899        99
+weighted avg     0.9901    0.9899    0.9899        99
+
+

Metrics

+
+
    +
  • True Positives (TP): 50
    • +
  • True Negatives (TN): 48
    • +
+
    +
  • False Positives (FP): 0
    • +
  • False Negatives (FN): 1
    • +
+
+
+
+

Confusion Matrix

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