Mercurial > repos > goeckslab > tabular_learner
comparison pycaret_regression.py @ 0:209b663a4f62 draft
planemo upload for repository https://github.com/goeckslab/gleam commit 5dd048419fcbd285a327f88267e93996cd279ee6
| author | goeckslab |
|---|---|
| date | Wed, 18 Jun 2025 15:38:19 +0000 |
| parents | |
| children | 11fdac5affb3 |
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| -1:000000000000 | 0:209b663a4f62 |
|---|---|
| 1 import logging | |
| 2 | |
| 3 from base_model_trainer import BaseModelTrainer | |
| 4 from dashboard import generate_regression_explainer_dashboard | |
| 5 from pycaret.regression import RegressionExperiment | |
| 6 from utils import add_hr_to_html, add_plot_to_html | |
| 7 | |
| 8 LOG = logging.getLogger(__name__) | |
| 9 | |
| 10 | |
| 11 class RegressionModelTrainer(BaseModelTrainer): | |
| 12 def __init__( | |
| 13 self, | |
| 14 input_file, | |
| 15 target_col, | |
| 16 output_dir, | |
| 17 task_type, | |
| 18 random_seed, | |
| 19 test_file=None, | |
| 20 **kwargs): | |
| 21 super().__init__( | |
| 22 input_file, | |
| 23 target_col, | |
| 24 output_dir, | |
| 25 task_type, | |
| 26 random_seed, | |
| 27 test_file, | |
| 28 **kwargs) | |
| 29 self.exp = RegressionExperiment() | |
| 30 | |
| 31 def save_dashboard(self): | |
| 32 LOG.info("Saving explainer dashboard") | |
| 33 dashboard = generate_regression_explainer_dashboard(self.exp, | |
| 34 self.best_model) | |
| 35 dashboard.save_html("dashboard.html") | |
| 36 | |
| 37 def generate_plots(self): | |
| 38 LOG.info("Generating and saving plots") | |
| 39 plots = ['residuals', 'error', 'cooks', | |
| 40 'learning', 'vc', 'manifold', | |
| 41 'rfe', 'feature', 'feature_all'] | |
| 42 for plot_name in plots: | |
| 43 try: | |
| 44 plot_path = self.exp.plot_model(self.best_model, | |
| 45 plot=plot_name, save=True) | |
| 46 self.plots[plot_name] = plot_path | |
| 47 except Exception as e: | |
| 48 LOG.error(f"Error generating plot {plot_name}: {e}") | |
| 49 continue | |
| 50 | |
| 51 def generate_plots_explainer(self): | |
| 52 LOG.info("Generating and saving plots from explainer") | |
| 53 | |
| 54 from explainerdashboard import RegressionExplainer | |
| 55 | |
| 56 X_test = self.exp.X_test_transformed.copy() | |
| 57 y_test = self.exp.y_test_transformed | |
| 58 | |
| 59 try: | |
| 60 explainer = RegressionExplainer(self.best_model, X_test, y_test) | |
| 61 self.expaliner = explainer | |
| 62 plots_explainer_html = "" | |
| 63 except Exception as e: | |
| 64 LOG.error(f"Error creating explainer: {e}") | |
| 65 self.plots_explainer_html = None | |
| 66 return | |
| 67 | |
| 68 try: | |
| 69 fig_importance = explainer.plot_importances() | |
| 70 plots_explainer_html += add_plot_to_html(fig_importance) | |
| 71 plots_explainer_html += add_hr_to_html() | |
| 72 except Exception as e: | |
| 73 LOG.error(f"Error generating plot importance: {e}") | |
| 74 | |
| 75 try: | |
| 76 fig_importance_permutation = \ | |
| 77 explainer.plot_importances_permutation( | |
| 78 kind="permutation") | |
| 79 plots_explainer_html += add_plot_to_html( | |
| 80 fig_importance_permutation) | |
| 81 plots_explainer_html += add_hr_to_html() | |
| 82 except Exception as e: | |
| 83 LOG.error(f"Error generating plot importance permutation: {e}") | |
| 84 | |
| 85 try: | |
| 86 for feature in self.features_name: | |
| 87 fig_shap = explainer.plot_pdp(feature) | |
| 88 plots_explainer_html += add_plot_to_html(fig_shap) | |
| 89 plots_explainer_html += add_hr_to_html() | |
| 90 except Exception as e: | |
| 91 LOG.error(f"Error generating plot shap dependence: {e}") | |
| 92 | |
| 93 # try: | |
| 94 # for feature in self.features_name: | |
| 95 # fig_interaction = explainer.plot_interaction(col=feature) | |
| 96 # plots_explainer_html += add_plot_to_html(fig_interaction) | |
| 97 # except Exception as e: | |
| 98 # LOG.error(f"Error generating plot shap interaction: {e}") | |
| 99 | |
| 100 try: | |
| 101 for feature in self.features_name: | |
| 102 fig_interactions_importance = \ | |
| 103 explainer.plot_interactions_importance( | |
| 104 col=feature) | |
| 105 plots_explainer_html += add_plot_to_html( | |
| 106 fig_interactions_importance) | |
| 107 plots_explainer_html += add_hr_to_html() | |
| 108 except Exception as e: | |
| 109 LOG.error(f"Error generating plot shap summary: {e}") | |
| 110 | |
| 111 # Regression specific plots | |
| 112 try: | |
| 113 fig_pred_actual = explainer.plot_predicted_vs_actual() | |
| 114 plots_explainer_html += add_plot_to_html(fig_pred_actual) | |
| 115 plots_explainer_html += add_hr_to_html() | |
| 116 except Exception as e: | |
| 117 LOG.error(f"Error generating plot prediction vs actual: {e}") | |
| 118 | |
| 119 try: | |
| 120 fig_residuals = explainer.plot_residuals() | |
| 121 plots_explainer_html += add_plot_to_html(fig_residuals) | |
| 122 plots_explainer_html += add_hr_to_html() | |
| 123 except Exception as e: | |
| 124 LOG.error(f"Error generating plot residuals: {e}") | |
| 125 | |
| 126 try: | |
| 127 for feature in self.features_name: | |
| 128 fig_residuals_vs_feature = \ | |
| 129 explainer.plot_residuals_vs_feature(feature) | |
| 130 plots_explainer_html += add_plot_to_html( | |
| 131 fig_residuals_vs_feature) | |
| 132 plots_explainer_html += add_hr_to_html() | |
| 133 except Exception as e: | |
| 134 LOG.error(f"Error generating plot residuals vs feature: {e}") | |
| 135 | |
| 136 self.plots_explainer_html = plots_explainer_html |
