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')