feat: add max_depth, C, test_size, random_state parameters to train endpoint
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2 changed files with 49 additions and 8 deletions
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@ -135,6 +135,7 @@ async def train(
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test_size: float = Form(0.2),
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random_state: int = Form(42),
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n_estimators: int = Form(100),
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max_depth: str = Form(""), # Empty string means None
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kernel: str = Form("linear"),
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C: float = Form(1.0),
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):
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@ -182,6 +183,7 @@ async def train(
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strategy,
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{
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"n_estimators": n_estimators,
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"max_depth": int(max_depth) if max_depth else None,
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"kernel": kernel,
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"C": C,
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"random_state": random_state,
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@ -34,6 +34,7 @@
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padding: 20px;
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overflow-y: auto;
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border-right: 1px solid #0f3460;
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color: #e0e0e0;
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}
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.sidebar h1 {
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@ -45,11 +46,20 @@
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.sidebar h2 {
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font-size: 1.1rem;
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margin: 20px 0 10px;
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color: #0f3460;
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color: #ff6b6b;
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border-bottom: 2px solid #e94560;
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padding-bottom: 5px;
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}
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.sidebar h3 {
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color: #ff8e8e;
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font-size: 0.95rem;
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}
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.sidebar p {
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color: #c0c0c0;
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}
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.form-group {
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margin-bottom: 15px;
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}
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@ -58,7 +68,8 @@
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display: block;
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margin-bottom: 5px;
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font-size: 0.9rem;
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color: #aaa;
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color: #ccc;
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font-weight: 500;
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}
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.form-group input,
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@ -79,7 +90,7 @@
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.form-group small {
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display: block;
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margin-top: 3px;
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color: #666;
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color: #888;
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font-size: 0.8rem;
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}
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@ -337,7 +348,33 @@
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</select>
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</div>
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<h2>3. Train & Classify</h2>
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<div class="form-group">
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<label for="maxDepth">Max Depth (Random Forest, optional)</label>
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<input type="number" id="maxDepth" value="" min="1" max="100" placeholder="None (auto)">
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<small>Leave empty for automatic depth</small>
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</div>
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<div class="form-group">
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<label for="cValue">C Parameter (SVM, Logistic Regression)</label>
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<input type="number" id="cValue" value="1.0" min="0.001" step="0.1">
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<small>Regularization strength (default: 1.0)</small>
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</div>
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<h3 style="color: #0f3460; margin: 20px 0 10px; font-size: 1rem;">Training Parameters</h3>
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<div class="form-group">
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<label for="testSize">Validation Split</label>
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<input type="number" id="testSize" value="0.2" min="0.1" max="0.5" step="0.05">
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<small>Fraction of data for validation (default: 0.2)</small>
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</div>
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<div class="form-group">
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<label for="randomState">Random Seed</label>
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<input type="number" id="randomState" value="42">
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<small>For reproducibility (default: 42)</small>
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</div>
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<h2>3. Train classifier</h2>
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<button class="btn btn-primary" id="trainBtn" onclick="train()">
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Train Model
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</button>
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@ -369,7 +406,7 @@
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</div>
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</div>
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<h2>4. Class Templates</h2>
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<h2>4. Classify and visualize</h2>
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<div class="form-group">
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<label for="templateSelect">Load Template</label>
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<select id="templateSelect" onchange="loadTemplate()">
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@ -521,8 +558,10 @@
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formData.append('class_column', document.getElementById('classColumn').value);
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formData.append('n_estimators', document.getElementById('nEstimators').value);
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formData.append('kernel', document.getElementById('kernel').value);
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formData.append('test_size', '0.2');
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formData.append('random_state', '42');
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formData.append('max_depth', document.getElementById('maxDepth').value || '');
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formData.append('C', document.getElementById('cValue').value);
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formData.append('test_size', document.getElementById('testSize').value);
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formData.append('random_state', document.getElementById('randomState').value);
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const trainBtn = document.getElementById('trainBtn');
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trainBtn.disabled = true;
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