348 lines
121 KiB
HTML
348 lines
121 KiB
HTML
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<!DOCTYPE html>
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<html lang="vi">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Training Report - 20260105_124348</title>
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<style>
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* {
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margin: 0;
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padding: 0;
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box-sizing: border-box;
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}
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body {
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font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
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background: #f5f5f5;
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padding: 20px;
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line-height: 1.6;
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}
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.container {
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max-width: 1200px;
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margin: 0 auto;
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background: white;
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border-radius: 15px;
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box-shadow: 0 10px 40px rgba(0,0,0,0.1);
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overflow: hidden;
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}
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.header {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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color: white;
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padding: 40px;
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text-align: center;
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}
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.header h1 {
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font-size: 2.5em;
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margin-bottom: 10px;
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}
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.header .subtitle {
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opacity: 0.9;
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font-size: 1.1em;
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}
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.content {
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padding: 40px;
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}
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.section {
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margin-bottom: 40px;
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}
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.section h2 {
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color: #667eea;
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border-bottom: 3px solid #667eea;
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padding-bottom: 10px;
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margin-bottom: 20px;
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font-size: 1.5em;
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}
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.stats-grid {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
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gap: 20px;
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margin-bottom: 30px;
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}
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.stat-card {
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background: linear-gradient(135deg, #667eea15 0%, #764ba215 100%);
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padding: 25px;
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border-radius: 10px;
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text-align: center;
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border: 1px solid #667eea30;
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}
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.stat-card .value {
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font-size: 2.5em;
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font-weight: bold;
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color: #667eea;
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}
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.stat-card .label {
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color: #666;
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margin-top: 5px;
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}
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.stat-card.success .value {
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color: #28a745;
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}
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.stat-card.warning .value {
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color: #ffc107;
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}
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table {
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width: 100%;
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border-collapse: collapse;
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margin: 20px 0;
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}
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th, td {
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padding: 12px 15px;
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text-align: left;
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border-bottom: 1px solid #ddd;
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}
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th {
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background: #667eea;
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color: white;
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}
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tr:hover {
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background-color: #f5f5f5;
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}
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.conf-matrix {
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font-size: 14px;
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}
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.conf-matrix th, .conf-matrix td {
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text-align: center;
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padding: 8px;
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}
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.chart-container {
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text-align: center;
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margin: 20px 0;
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}
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.chart-container img {
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max-width: 100%;
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border-radius: 10px;
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box-shadow: 0 4px 15px rgba(0,0,0,0.1);
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}
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.info-box {
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background: #e3f2fd;
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padding: 20px;
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border-radius: 10px;
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border-left: 5px solid #2196f3;
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margin: 20px 0;
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}
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.info-row {
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display: flex;
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margin: 10px 0;
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}
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.info-label {
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font-weight: bold;
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width: 200px;
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color: #555;
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}
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.info-value {
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color: #333;
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}
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.footer {
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background: #f8f9fa;
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padding: 20px;
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text-align: center;
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color: #666;
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font-size: 14px;
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}
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@media print {
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body {
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background: white;
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padding: 0;
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}
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.container {
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box-shadow: none;
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}
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}
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</style>
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</head>
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<body>
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<div class="container">
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<div class="header">
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<h1>📊 Báo Cáo Training Model</h1>
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<p class="subtitle">Land Classification - 05/01/2026 12:43:49</p>
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</div>
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<div class="content">
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<!-- Summary Stats -->
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<div class="section">
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<h2>📈 Tóm Tắt Kết Quả</h2>
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<div class="stats-grid">
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<div class="stat-card success">
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<div class="value">100.0%</div>
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<div class="label">Train Accuracy</div>
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</div>
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<div class="stat-card warning">
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<div class="value">75.7%</div>
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<div class="label">Test Accuracy</div>
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</div>
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<div class="stat-card">
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<div class="value">868</div>
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<div class="label">Training Samples</div>
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</div>
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<div class="stat-card">
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<div class="value">218</div>
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<div class="label">Testing Samples</div>
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</div>
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<div class="stat-card">
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<div class="value">8</div>
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<div class="label">Số Classes</div>
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</div>
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<div class="stat-card">
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<div class="value">20%</div>
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<div class="label">Test Size</div>
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</div>
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</div>
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</div>
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<!-- Configuration Info -->
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<div class="section">
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<h2>⚙️ Cấu Hình Training</h2>
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<div class="info-box">
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<div class="info-row">
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<span class="info-label">🤖 Model Type:</span>
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<span class="info-value">XGBOOST</span>
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</div>
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<div class="info-row">
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<span class="info-label">📍 Khu vực (bbox):</span>
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<span class="info-value">[105.561448, 9.264228, 106.298669, 9.931334]</span>
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</div>
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<div class="info-row">
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<span class="info-label">📅 Thời gian:</span>
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<span class="info-value">2023-03-01/2023-12-31</span>
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</div>
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<div class="info-row">
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<span class="info-label">📐 Độ phân giải:</span>
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<span class="info-value">20m</span>
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</div>
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<div class="info-row">
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<span class="info-label">💾 Model Path:</span>
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<span class="info-value">model_train/model_xgboost_20260105_123120.joblib</span>
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</div>
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</div>
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</div>
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<!-- Classification Report -->
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<div class="section">
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<h2>📋 Classification Report</h2>
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<table>
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<thead>
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<tr>
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<th>Loại đất</th>
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<th>Precision</th>
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<th>Recall</th>
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<th>F1-Score</th>
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<th>Support</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><strong>0</strong></td>
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<td>0.667</td>
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<td>0.500</td>
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<td>0.571</td>
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<td>12</td>
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</tr>
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<tr>
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<td><strong>1</strong></td>
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<td>0.698</td>
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<td>0.732</td>
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<td>0.714</td>
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<td>41</td>
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</tr>
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<tr>
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<td><strong>2</strong></td>
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<td>0.375</td>
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<td>0.333</td>
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<td>0.353</td>
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<td>9</td>
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</tr>
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<tr>
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<td><strong>3</strong></td>
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<td>0.656</td>
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<td>0.618</td>
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<td>0.636</td>
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<td>34</td>
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</tr>
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<tr>
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<td><strong>4</strong></td>
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<td>0.724</td>
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<td>0.808</td>
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<td>0.764</td>
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<td>26</td>
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</tr>
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<tr>
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<td><strong>5</strong></td>
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<td>0.963</td>
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<td>1.000</td>
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<td>0.981</td>
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<td>26</td>
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</tr>
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<tr>
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<td><strong>6</strong></td>
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<td>0.886</td>
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<td>0.886</td>
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<td>0.886</td>
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<td>44</td>
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</tr>
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<tr>
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<td><strong>7</strong></td>
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<td>0.731</td>
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<td>0.731</td>
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<td>0.731</td>
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<td>26</td>
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</tr>
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<tr style="background-color: #f0f0f0; font-weight: bold;">
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<td>macro avg</td>
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<td>0.712</td>
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<td>0.701</td>
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<td>0.705</td>
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<td>218</td>
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</tr>
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<tr style="background-color: #f0f0f0; font-weight: bold;">
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<td>weighted avg</td>
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<td>0.753</td>
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<td>0.757</td>
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<td>0.754</td>
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<td>218</td>
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</tr>
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</tbody>
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</table>
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</div>
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<!-- Metrics Chart -->
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<div class="section"><h2>📊 Biểu Đồ Metrics</h2><div class="chart-container"><img 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" alt="Metrics Chart"></div></div>
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<div class="section"><h2>📊 Phân Bố Số Mẫu</h2><div class="chart-container"><img 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" alt="Class Distribution"></div></div>
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<!-- Confusion Matrix -->
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<div class="section">
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<h2>🔢 Confusion Matrix</h2>
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<div class="chart-container"><img 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" alt="Confusion Matrix"></div>
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</div>
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<!-- Classes List -->
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<div class="section">
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<h2>🏷️ Danh Sách Các Loại Đất</h2>
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<div class="info-box">
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<ul style="list-style: none; display: flex; flex-wrap: wrap; gap: 10px;">
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<li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">0</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">1</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">2</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">3</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">4</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">5</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">6</li><li style="background: #667eea; color: white; padding: 8px 15px; border-radius: 20px;">7</li>
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</ul>
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</div>
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</div>
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</div>
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<div class="footer">
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<p>🌍 Land Classification Training System | Generated: 05/01/2026 12:43:49</p>
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<p>Data Source: Microsoft Planetary Computer (Sentinel-2 L2A, Sentinel-1 RTC)</p>
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</div>
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</div>
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</body>
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</html>
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