KNN.py

#coding=utf-8
#chapter 2 
#code 4
from sklearn.datasets import load_iris
from sklearn.cross_validation import train_test_split
from sklearn.preprocessing import StandardScaler
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import classification_report

iris=load_iris()
#print(iris.data.shape)
#print(iris.DESCR)
X_train, X_test, y_train, y_test=train_test_split(iris.data,iris.target,test_size=0.25,random_state=33)
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))
print(classification_report(y_test,y_predict,target_names=iris.target_names))