3 # -*- coding: utf-8 -*-
4 from sklearn
.cross_validation
import KFold
5 from sklearn
import neighbors
6 from sklearn
.datasets
import load_iris
12 kf
= KFold(len(X
), n_folds
=10, shuffle
=True)
15 for k
in range(1, 30):
17 clf
= neighbors
.KNeighborsClassifier(k
)
18 for learn
, test
in kf
:
19 X_train
= [X
[i
] for i
in learn
]
20 Y_train
= [Y
[i
] for i
in learn
]
21 clf
.fit(X_train
, Y_train
)
22 X_test
= [X
[i
] for i
in test
]
23 Y_test
= [Y
[i
] for i
in test
]
24 score
= score
+ clf
.score(X_test
, Y_test
)
28 print("meilleure valeur pour k : ", scores
.index(max(scores
)) + 1)