plot_cross_val_confusion_matrix( ml_5_svm, x_5, y_5, display_labels=('team loses', 'draw', 'team wins'), title='Support Vector Machine Confusion Matrix ML5', cv=skf) if save_conf_matrix_df5: plt.savefig('figures\ml_5_confusion_matrix_cross_val_svm.png') # ---------- LEARNING CURVE PLOTS ---------- plot_learning_curve(ml_10_svm, x_10, y_10, training_set_size=10, x_max=160, title='Learning Curve - Support Vector Machine DF_10', leg_loc=1) if save_learning_curve_df10: plt.savefig('figures\ml_10_svm_learning_curve.png') plot_learning_curve(ml_5_svm, x_5, y_5, training_set_size=10, x_max=230, title='Learning Curve - Support Vector Machine DF_5', leg_loc=1) if save_learning_curve_df5: plt.savefig('figures\ml_5_svm_learning_curve.png')
plot_cross_val_confusion_matrix(ml_5_rand_forest, x_5, y_5, display_labels=('team loses', 'draw', 'team wins'), title='Random Forest Confusion Matrix ML5', cv=skf) if save_conf_matrix_df5: plt.savefig('figures\ml_5_confusion_matrix_cross_val_random_forest.png') # ---------- LEARNING CURVE PLOTS ---------- plot_learning_curve(ml_10_rand_forest, x_10, y_10, training_set_size=20, x_max=160, title='Learning Curve - Random Forest DF_10') if save_learning_curve_df10: plt.savefig('figures\ml_10_random_forest_learning_curve.png') plot_learning_curve(ml_5_rand_forest, x_5, y_5, training_set_size=20, x_max=190, title='Learning Curve - Random Forest DF_5') if save_learning_curve_df5: plt.savefig('figures\ml_5_random_forest_learning_curve.png') # ---------- FEATURE IMPORTANCE ----------
plot_cross_val_confusion_matrix(ml_5_knn, x_5, y_5, display_labels=('team loses', 'draw', 'team wins'), title='Nearest Neighbor Confusion Matrix ML5', cv=skf) if save_conf_matrix_df5: plt.savefig('figures\ml_5_confusion_matrix_cross_val_nearest_neighbor.png') # ---------- LEARNING CURVE PLOTS ---------- plot_learning_curve(ml_10_knn, x_10, y_10, training_set_size=10, x_max=160, title='Learning Curve - Nearest Neighbor DF_10', leg_loc=1) if save_learning_curve_df10: plt.savefig('figures\ml_10_nearest_neighbor_learning_curve.png') plot_learning_curve(ml_5_knn, x_5, y_5, training_set_size=10, x_max=230, title='Learning Curve - Nearest Neighbor DF_5', leg_loc=1) if save_learning_curve_df5: plt.savefig('figures\ml_5_nearest_neighbor_learning_curve.png')