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a2dbe57 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 | <!DOCTYPE html>
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<title>Credily Training Report</title>
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<header>
<h1>Credily Training Report</h1>
<p>Generated: 2026-01-03 00:14:50</p>
</header>
<section class="card">
<h2>Model Performance</h2>
<div class="best-model">
<h3>Best Model: RandomForest</h3>
<div class="score">ROC-AUC: 0.8029</div>
<p>Test AUC: 0.3958</p>
</div>
<h3>Model Comparison</h3>
<table>
<thead><tr><th>Model</th><th>CV ROC-AUC</th></tr></thead>
<tbody><tr ><td>LogisticRegression</td><td>0.6318</td></tr><tr style="background-color: #d4edda; font-weight: bold;"><td>RandomForest</td><td>0.8029</td></tr><tr ><td>GradientBoosting</td><td>0.7847</td></tr></tbody>
</table>
</section>
<section class="card">
<h2>Classification Report</h2>
<table>
<thead>
<tr><th>Class</th><th>Precision</th><th>Recall</th><th>F1-Score</th><th>Support</th></tr>
</thead>
<tbody><tr>
<td>0.0</td>
<td>0.333</td>
<td>0.014</td>
<td>0.027</td>
<td>71.0</td>
</tr><tr>
<td>1.0</td>
<td>0.278</td>
<td>0.931</td>
<td>0.429</td>
<td>29.0</td>
</tr><tr>
<td>macro avg</td>
<td>0.306</td>
<td>0.473</td>
<td>0.228</td>
<td>100.0</td>
</tr><tr>
<td>weighted avg</td>
<td>0.317</td>
<td>0.280</td>
<td>0.143</td>
<td>100.0</td>
</tr></tbody>
</table>
</section>
<section class="card">
<h2>Feature Importance (Top 20)</h2>
<table>
<thead><tr><th>Feature</th><th>Importance</th></tr></thead>
<tbody><tr><td>income</td><td>0.2097</td></tr><tr><td>loan_amount</td><td>0.1800</td></tr><tr><td>debt_ratio</td><td>0.1800</td></tr><tr><td>age</td><td>0.1726</td></tr><tr><td>credit_score</td><td>0.1565</td></tr><tr><td>income_missing</td><td>0.0517</td></tr><tr><td>credit_score_missing</td><td>0.0284</td></tr><tr><td>employment_status_missing</td><td>0.0212</td></tr><tr><td>employment_status_nan</td><td>0.0000</td></tr><tr><td>education_nan</td><td>0.0000</td></tr><tr><td>home_ownership_nan</td><td>0.0000</td></tr></tbody>
</table>
</section>
<footer>
<p>Generated by Credily - Fast, Explainable AutoML for Tabular Data</p>
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