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from sklearn.metrics import accuracy_score, f1_score | |
def get_metrics(y_true, y_preds): | |
accuracy = accuracy_score(y_true, y_preds) | |
f1_macro = f1_score(y_true, y_preds, average="macro") | |
f1_weighted = f1_score(y_true, y_preds, average="weighted") | |
print(f"Accuracy: {accuracy}") | |
print(f"F1 macro average: {f1_macro}") | |
print(f"F1 weighted average: {f1_weighted}") | |
def evaluate_predictions(model:str, train_preds, y_train, test_preds, y_test): | |
print(model) | |
print("\nTrain set:") | |
get_metrics(y_train, train_preds) | |
print("-"*50) | |
print("Test set:") | |
get_metrics(y_test, test_preds) |