diff --git "a/A2/ml_experiments.ipynb" "b/A2/ml_experiments.ipynb" --- "a/A2/ml_experiments.ipynb" +++ "b/A2/ml_experiments.ipynb" @@ -1618,9 +1618,28 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 18, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "====================================================================================================\n", + "COMPREHENSIVE MODEL COMPARISON\n", + "====================================================================================================\n", + " Model Features Train_R2 Test_R2 Test_RMSE Test_MAE Overfitting_Gap Delta_R2_vs_Baseline Delta_RMSE_vs_Baseline Feature_Reduction_%\n", + "Baseline (All Features) 36 0.615644 0.486390 0.160148 0.122159 0.129254 0.000000 0.000000 0.000000\n", + " Correlation-Based 35 0.614036 0.484176 0.160493 0.121970 0.129861 -0.002214 0.000345 2.777778\n", + " RFE (25 features) 25 0.613436 0.487558 0.159966 0.122606 0.125879 0.001168 -0.000182 30.555556\n", + " Lasso Regularization 35 0.615077 0.489988 0.159586 0.121623 0.125089 0.003598 -0.000562 2.777778\n", + " Polynomial (Degree 2) 665 0.901480 0.206907 0.199006 0.148560 0.694574 -0.279483 0.038858 -1747.222222\n", + " Symmetry-Constrained 36 0.598918 0.492318 0.159221 0.120716 0.106601 0.005928 -0.000927 0.000000\n", + "====================================================================================================\n" + ] + } + ], "source": [ "# Compile all results\n", "results_summary = pd.DataFrame({\n", @@ -1696,9 +1715,20 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "# Visualize comparison\n", "fig = plt.figure(figsize=(18, 12))\n", @@ -1784,9 +1814,70 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 20, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "====================================================================================================\n", + "KEY FINDINGS & RECOMMENDATIONS\n", + "====================================================================================================\n", + "\n", + "1️⃣ BEST OVERALL MODEL (Highest Test R²)\n", + " Model: Symmetry-Constrained\n", + " Test R²: 0.4923\n", + " Improvement: +0.0059 vs baseline\n", + " Features: 36 (0.0% reduction)\n", + " RMSE: 0.1592\n", + " Overfitting Gap: 0.1066\n", + "\n", + "2️⃣ BEST GENERALIZATION (Lowest Overfitting Gap)\n", + " Model: Symmetry-Constrained\n", + " Overfitting Gap: 0.1066\n", + " Test R²: 0.4923\n", + " Features: 36\n", + " ⚠ Moderate generalization\n", + "\n", + "3️⃣ MOST EFFICIENT (Best R² per Feature)\n", + " Model: RFE (25 features)\n", + " Test R²: 0.4876\n", + " Features: 25 (30.6% reduction)\n", + " Efficiency score: 0.7021\n", + "\n", + "4️⃣ SIMPLEST MODEL (Fewest Features)\n", + " Model: RFE (25 features)\n", + " Features: 25 (30.6% reduction)\n", + " Test R²: 0.4876\n", + " R² retention: 100.2% of baseline\n", + "\n", + "5️⃣ FEATURE SELECTION EFFECTIVENESS\n", + " Baseline features: 36\n", + " Average reduction across methods: -285.2%\n", + " Best reduction: 30.6% (RFE (25 features))\n", + " Average R² across all models: 0.4412\n", + " R² std dev: 0.1148\n", + "\n", + "6️⃣ RECOMMENDATIONS FOR DEPLOYMENT\n", + " ✓ RECOMMENDED: Symmetry-Constrained\n", + " - Excellent generalization even if slightly lower accuracy\n", + "\n", + "7️⃣ AVOID IN PRODUCTION\n", + " ✗ Polynomial features - High overfitting risk (0.6946 gap)\n", + "\n", + "8️⃣ NEXT STEPS\n", + " 1. Choose champion model: Symmetry-Constrained\n", + " 2. Validate with cross-validation (5-fold)\n", + " 3. Test on hold-out validation set\n", + " 4. Deploy as REST API service\n", + " 5. Monitor performance on new movement data\n", + "\n", + "====================================================================================================\n" + ] + } + ], "source": [ "# Key findings and recommendations\n", "print(\"\\n\" + \"=\"*100)\n", @@ -1878,9 +1969,37 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 21, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "====================================================================================================\n", + "ROBUSTNESS CHECK: 5-FOLD CROSS-VALIDATION\n", + "====================================================================================================\n", + "\n", + "Baseline:\n", + " CV R² (mean ± std): 0.5809 ± 0.0546\n", + " CV RMSE (mean ± std): 0.1550 ± 0.0467\n", + " Fold scores: ['0.5809', '0.4796', '0.6244', '0.5864', '0.6331']\n", + "\n", + "Lasso:\n", + " CV R² (mean ± std): 0.5834 ± 0.0502\n", + " CV RMSE (mean ± std): 0.1546 ± 0.0449\n", + " Fold scores: ['0.5857', '0.4903', '0.6231', '0.5863', '0.6317']\n", + "\n", + "Symmetry:\n", + " CV R² (mean ± std): 0.5789 ± 0.0574\n", + " CV RMSE (mean ± std): 0.1553 ± 0.0462\n", + " Fold scores: ['0.5666', '0.4746', '0.6245', '0.5939', '0.6348']\n", + "\n", + "====================================================================================================\n" + ] + } + ], "source": [ "# Cross-validation for robustness check\n", "from sklearn.model_selection import cross_validate\n",