#Naive Bayes

from sklearn.model_selection import train_test_split
from sklearn.naive_bayes import GaussianNB
from sklearn.datasets import load_iris
from sklearn.metrics import accuracy_score, confusion_matrix, classification_report

data = load_iris()
X = data.data
y = (data.target == 2).astype(int)

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.3, random_state = 0)


model = GaussianNB()
model.fit(X_train, y_train)

y_pred = model.predict(X_test)

accuracy = accuracy_score(y_test, y_pred)
conf = confusion_matrix(y_test, y_pred)
classR = classification_report(y_test, y_pred)

print(accuracy)
print(conf)
print(classR)