4daa73f4dc91a3e9bb1d555b53a97f4e738a2fe6
3 # -*- coding: utf-8 -*-
5 from sklearn
import neighbors
6 from sklearn
.cross_validation
import train_test_split
7 from sklearn
.datasets
import load_iris
14 # print(help(train_test_split))
15 X_train
, X_test
, Y_train
, Y_test
= train_test_split(
16 X
, Y
, test_size
=0.3, random_state
=random
.seed())
19 # print(len(X_train[Y_train == 0]))
20 # print(len(X_train[Y_train == 1]))
21 # print(len(X_train[Y_train == 2]))
24 clf
= neighbors
.KNeighborsClassifier(nb_voisins
)
25 clf
.fit(X_train
, Y_train
)
26 # print("kNN prediction on [5.4, 3.2, 1.6, 0.4]:")
27 # print(clf.predict([[5.4, 3.2, 1.6, 0.4]]))
28 # print("kNN probability prediction on [5.4, 3.2, 1.6, 0.4]:")
29 # print(clf.predict_proba([[5.4, 3.2, 1.6, 0.4]]))
30 print("kNN score on Iris test data:")
31 print(clf
.score(X_test
, Y_test
))
32 print("kNN prediction error(s) on Iris test data:")
33 Z
= clf
.predict(X_test
)
34 print(X_test
[Z
!= Y_test
])