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<html>
<head>
<title>GENE_FAMILY: Trihelix</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=Trihelix' target='_blank'>Trihelix</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) │ 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)
</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 6256 50.1
0 6231 49.9</pre>
<h3>Additional Metrics</h3>
<ul>
<li>Total Samples: 12487</li>
<li>Imbalance Ratio: 1.00</li>
</ul>
</div>
<div class="section">
<h2>Classification Report</h2>
<pre> precision recall f1-score support
Class 0 0.9678 0.9896 0.9786 1246
Class 1 0.9894 0.9673 0.9782 1252
accuracy 0.9784 2498
macro avg 0.9786 0.9784 0.9784 2498
weighted avg 0.9786 0.9784 0.9784 2498
</pre>
<h3>Metrics</h3>
<div class="metrics">
<ul>
<li>True Positives (TP): 1211</li>
<li>True Negatives (TN): 1233</li>
</ul>
<ul>
<li>False Positives (FP): 13</li>
<li>False Negatives (FN): 41</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) │ 2,295,296 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ 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: 7,015,685 (26.76 MB)
Trainable params: 2,338,561 (8.92 MB)
Non-trainable params: 0 (0.00 B)
Optimizer params: 4,677,124 (17.84 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 6256 50.1
0 6231 49.9</pre>
<h3>Additional Metrics</h3>
<ul>
<li>Total Samples: 12487</li>
<li>Imbalance Ratio: 1.00</li>
</ul>
</div>
<div class="section">
<h2>Classification Report</h2>
<pre> precision recall f1-score support
Class 0 0.9944 0.9968 0.9956 1246
Class 1 0.9968 0.9944 0.9956 1252
accuracy 0.9956 2498
macro avg 0.9956 0.9956 0.9956 2498
weighted avg 0.9956 0.9956 0.9956 2498
</pre>
<h3>Metrics</h3>
<div class="metrics">
<ul>
<li>True Positives (TP): 1245</li>
<li>True Negatives (TN): 1242</li>
</ul>
<ul>
<li>False Positives (FP): 4</li>
<li>False Negatives (FN): 7</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) │ 40,006,656 │
├──────────────────────────────────────┼─────────────────────────────┼─────────────────┤
│ 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: 120,143,621 (458.31 MB)
Trainable params: 40,047,873 (152.77 MB)
Non-trainable params: 0 (0.00 B)
Optimizer params: 80,095,748 (305.54 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 6256 50.1
0 6231 49.9</pre>
<h3>Additional Metrics</h3>
<ul>
<li>Total Samples: 12487</li>
<li>Imbalance Ratio: 1.00</li>
</ul>
</div>
<div class="section">
<h2>Classification Report</h2>
<pre> precision recall f1-score support
Class 0 0.9928 1.0000 0.9964 1246
Class 1 1.0000 0.9928 0.9964 1252
accuracy 0.9964 2498
macro avg 0.9964 0.9964 0.9964 2498
weighted avg 0.9964 0.9964 0.9964 2498
</pre>
<h3>Metrics</h3>
<div class="metrics">
<ul>
<li>True Positives (TP): 1243</li>
<li>True Negatives (TN): 1246</li>
</ul>
<ul>
<li>False Positives (FP): 0</li>
<li>False Negatives (FN): 9</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>
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