2.x ESL第二章习题 2.8

题目

代码

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import pandas as pd import numpy as np train_full=pd.read_csv('../zip.train',sep=' ',engine='c',header=None).values[:,0:-1] test_full=pd.read_csv('../zip.test',sep=' ',engine='c',header=None).values     train = np.vstack((train_full[train_full[:,0]==2],train_full[train_full[:,0]==3])) test = np.vstack((test_full[test_full[:,0]==2],test_full[test_full[:,0]==3]))     train_x=train[:,1:] train_y=train[:,0] test_x=test[:,1:] test_y=test[:,0]     dc = [] from sklearn.linear_model import LinearRegression lrcf = LinearRegression() lrcf.fit(train_x, train_y) dc.append(('linear regression',lrcf))     from sklearn.neighbors import KNeighborsClassifier for i in [1,3,5,7,15]:     knn = KNeighborsClassifier(n_neighbors=i)     knn.fit(train_x,train_y)     dc.append(('%d-nearest neighbor' %(i),knn))     def acc(clf,x,y):     res = clf.predict(x)     if type(clf)==LinearRegression:         res[res>2.5]=3         res[res<2.5]=2     n = y.shape[0]     r = res[(res==y)].shape[0]     return r*1.0/n     for i in dc:     accr = acc(i[1],test_x,test_y)     print '%s:  %.5f' %(i[0],accr)

结果

linear regression:  0.95879

1-nearest neighbor:  0.97527

3-nearest neighbor:  0.96978

5-nearest neighbor:  0.96978

7-nearest neighbor:  0.96703

15-nearest neighbor:  0.96154