# cross_val_score.py
# Show how to use the the cross_val_score function
# Dr. Pan, Dept. of ECE, UAH

from sklearn.naive_bayes import GaussianNB
clf = GaussianNB()

from sklearn.datasets import load_iris
train_samples = load_iris()
X = train_samples.data
Y = train_samples.target

from sklearn.model_selection import StratifiedKFold
KFold1 = StratifiedKFold(n_splits=10, random_state=1, shuffle=True)

from sklearn.model_selection import KFold
KFold2 = KFold(n_splits=10, random_state=1, shuffle=True)

from sklearn.model_selection import cross_val_score

scores1 = cross_val_score(clf, X, Y, cv = KFold1, scoring = 'accuracy')
import numpy as np
print(np.mean(scores1))

scores2 = cross_val_score(clf, X, Y, cv = KFold2, scoring = 'accuracy')
print(np.mean(scores2))