pythonではKNN実装によるirisの分類

from sklearn.datasets import load_iris

iris = load_iris()

print iris.data.shape

from sklearn.cross_validation import train_test_split

X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size = 0.25, random_state = 33)

from sklearn.preprocessing import StandardScaler
from sklearn.neighbors import KNeighborsClassifier

ss = StandardScaler()

X_train = ss.fit_transform(X_train)
X_test = ss.transform(X_test)

knc = KNeighborsClassifier()
knc.fit(X_train, y_train)
y_predict = knc.predict(X_test)

print 'The accuracy of K-Nearest Neighbor Classifier is: ', knc.score(X_test, y_test)

from sklearn.metrics import classification_report

print classification_report(y_test, y_predict, target_names = iris.target_names)