innitialize k fold cross validation

from sklearn.model_selection import KFold
from sklearn.model_selection import cross_val_score

model = RandomForestClassifier()

k_fold = KFold(n_splits=5, shuffle=True, random_state=42)

scores = cross_val_score(model, X_train, Y_train, cv=k_fold, scoring='accuracy')

for i, score in enumerate(scores, 1):
    print(f'Fold {i}: Accuracy = {score:.4f}')
    
print(f'Mean Accuracy: {np.mean(scores):.4f}')
print(f'Standard Deviation: {np.std(scores):.4f}')