| <html> | |
| <head> | |
| <title>GENE_FAMILY: Dof</title> | |
| <style> | |
| body { font-family: Arial, sans-serif; } | |
| .container { border: 2px solid #ddd; margin: 20px; padding: 20px; } | |
| .header { padding: 0.6em; background-color: #ffdddd; font-weight: bold; } | |
| .title { padding: 0.6em; background-color: #80c4e6bd; font-weight: bold; } | |
| .section { padding: 10px; } | |
| .metrics { display: flex; } | |
| .metrics ul { list-style: none; padding: 0; } | |
| .metrics ul + ul { margin-left: 2em; } | |
| .confusion-matrix img, .learning-curve img { width: 100%; max-width: 565px; } | |
| .class_dist { width: 20em; } | |
| .mod_sum { margin-bottom: 2em; } | |
| </style> | |
| </head> | |
| <body> | |
| <div class="container title"> | |
| <h3>GENE_FAMILY: <a href='https://planttfdb.gao-lab.org/family.php?fam=Dof' target='_blank'>Dof</a></h3> | |
| </div> | |
| <div class="container"> | |
| <div class="header">MODEL: FEEDFORWARD_k2</div> | |
| <div style="display: flex;"> | |
| <div class="section"> | |
| <h2 class='mod_sum'>Model Architecture</h2> | |
| <pre>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) | |
| </pre> | |
| </div> | |
| <div class="section learning-curve"> | |
| <h2>Learning Curve</h2> | |
| <img 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" alt="Learning Curve"> | |
| </div> | |
| </div> | |
| <div style="display: flex;"> | |
| <div class="section class_dist"> | |
| <h2>Class Distribution</h2> | |
| <pre> Count Percentage | |
| class | |
| 1 4524 50.13 | |
| 0 4500 49.87</pre> | |
| <h3>Additional Metrics</h3> | |
| <ul> | |
| <li>Total Samples: 9024</li> | |
| <li>Imbalance Ratio: 1.01</li> | |
| </ul> | |
| </div> | |
| <div class="section"> | |
| <h2>Classification Report</h2> | |
| <pre> precision recall f1-score support | |
| Class 0 0.9903 0.9947 0.9925 1126 | |
| Class 1 0.9947 0.9903 0.9925 1131 | |
| accuracy 0.9925 2257 | |
| macro avg 0.9925 0.9925 0.9925 2257 | |
| weighted avg 0.9925 0.9925 0.9925 2257 | |
| </pre> | |
| <h3>Metrics</h3> | |
| <div class="metrics"> | |
| <ul> | |
| <li>True Positives (TP): 1120</li> | |
| <li>True Negatives (TN): 1120</li> | |
| </ul> | |
| <ul> | |
| <li>False Positives (FP): 6</li> | |
| <li>False Negatives (FN): 11</li> | |
| </ul> | |
| </div> | |
| </div> | |
| <div class="section confusion-matrix"> | |
| <h2>Confusion Matrix</h2> | |
| <img src="data:image/png;base64,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" alt="Confusion Matrix"> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="container"> | |
| <div class="header">MODEL: FEEDFORWARD_k3</div> | |
| <div style="display: flex;"> | |
| <div class="section"> | |
| <h2 class='mod_sum'>Model Architecture</h2> | |
| <pre>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) | |
| </pre> | |
| </div> | |
| <div class="section learning-curve"> | |
| <h2>Learning Curve</h2> | |
| <img src="data:image/png;base64,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" alt="Learning Curve"> | |
| </div> | |
| </div> | |
| <div style="display: flex;"> | |
| <div class="section class_dist"> | |
| <h2>Class Distribution</h2> | |
| <pre> Count Percentage | |
| class | |
| 1 4524 50.13 | |
| 0 4500 49.87</pre> | |
| <h3>Additional Metrics</h3> | |
| <ul> | |
| <li>Total Samples: 9024</li> | |
| <li>Imbalance Ratio: 1.01</li> | |
| </ul> | |
| </div> | |
| <div class="section"> | |
| <h2>Classification Report</h2> | |
| <pre> precision recall f1-score support | |
| Class 0 0.9947 1.0000 0.9973 1126 | |
| Class 1 1.0000 0.9947 0.9973 1131 | |
| accuracy 0.9973 2257 | |
| macro avg 0.9973 0.9973 0.9973 2257 | |
| weighted avg 0.9974 0.9973 0.9973 2257 | |
| </pre> | |
| <h3>Metrics</h3> | |
| <div class="metrics"> | |
| <ul> | |
| <li>True Positives (TP): 1125</li> | |
| <li>True Negatives (TN): 1126</li> | |
| </ul> | |
| <ul> | |
| <li>False Positives (FP): 0</li> | |
| <li>False Negatives (FN): 6</li> | |
| </ul> | |
| </div> | |
| </div> | |
| <div class="section confusion-matrix"> | |
| <h2>Confusion Matrix</h2> | |
| <img src="data:image/png;base64,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" alt="Confusion Matrix"> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="container"> | |
| <div class="header">MODEL: FEEDFORWARD_k4</div> | |
| <div style="display: flex;"> | |
| <div class="section"> | |
| <h2 class='mod_sum'>Model Architecture</h2> | |
| <pre>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) | |
| </pre> | |
| </div> | |
| <div class="section learning-curve"> | |
| <h2>Learning Curve</h2> | |
| <img src="data:image/png;base64,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" alt="Learning Curve"> | |
| </div> | |
| </div> | |
| <div style="display: flex;"> | |
| <div class="section class_dist"> | |
| <h2>Class Distribution</h2> | |
| <pre> Count Percentage | |
| class | |
| 1 4524 50.13 | |
| 0 4500 49.87</pre> | |
| <h3>Additional Metrics</h3> | |
| <ul> | |
| <li>Total Samples: 9024</li> | |
| <li>Imbalance Ratio: 1.01</li> | |
| </ul> | |
| </div> | |
| <div class="section"> | |
| <h2>Classification Report</h2> | |
| <pre> precision recall f1-score support | |
| Class 0 0.9877 1.0000 0.9938 1126 | |
| Class 1 1.0000 0.9876 0.9938 1131 | |
| accuracy 0.9938 2257 | |
| macro avg 0.9939 0.9938 0.9938 2257 | |
| weighted avg 0.9939 0.9938 0.9938 2257 | |
| </pre> | |
| <h3>Metrics</h3> | |
| <div class="metrics"> | |
| <ul> | |
| <li>True Positives (TP): 1117</li> | |
| <li>True Negatives (TN): 1126</li> | |
| </ul> | |
| <ul> | |
| <li>False Positives (FP): 0</li> | |
| <li>False Negatives (FN): 14</li> | |
| </ul> | |
| </div> | |
| </div> | |
| <div class="section confusion-matrix"> | |
| <h2>Confusion Matrix</h2> | |
| <img src="data:image/png;base64,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" alt="Confusion Matrix"> | |
| </div> | |
| </div> | |
| </div> | |
| <div class="container"> | |
| <div class="header">MODEL: FEEDFORWARD_k5</div> | |
| <div style="display: flex;"> | |
| <div class="section"> | |
| <h2 class='mod_sum'>Model Architecture</h2> | |
| <pre>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) | |
| </pre> | |
| </div> | |
| <div class="section learning-curve"> | |
| <h2>Learning Curve</h2> | |
| <img src="data:image/png;base64,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" alt="Learning Curve"> | |
| </div> | |
| </div> | |
| <div style="display: flex;"> | |
| <div class="section class_dist"> | |
| <h2>Class Distribution</h2> | |
| <pre> Count Percentage | |
| class | |
| 1 4524 50.13 | |
| 0 4500 49.87</pre> | |
| <h3>Additional Metrics</h3> | |
| <ul> | |
| <li>Total Samples: 9024</li> | |
| <li>Imbalance Ratio: 1.01</li> | |
| </ul> | |
| </div> | |
| <div class="section"> | |
| <h2>Classification Report</h2> | |
| <pre> precision recall f1-score support | |
| Class 0 0.9903 1.0000 0.9951 1126 | |
| Class 1 1.0000 0.9903 0.9951 1131 | |
| accuracy 0.9951 2257 | |
| macro avg 0.9952 0.9951 0.9951 2257 | |
| weighted avg 0.9952 0.9951 0.9951 2257 | |
| </pre> | |
| <h3>Metrics</h3> | |
| <div class="metrics"> | |
| <ul> | |
| <li>True Positives (TP): 1120</li> | |
| <li>True Negatives (TN): 1126</li> | |
| </ul> | |
| <ul> | |
| <li>False Positives (FP): 0</li> | |
| <li>False Negatives (FN): 11</li> | |
| </ul> | |
| </div> | |
| </div> | |
| <div class="section confusion-matrix"> | |
| <h2>Confusion Matrix</h2> | |
| <img src="data:image/png;base64,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" alt="Confusion Matrix"> | |
| </div> | |
| </div> | |
| </div> | |
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