TP1/exo2/TP1prog4.py

   1 #!/usr/bin/env python3
   2
   3 # -*- coding: utf-8 -*-
   4 from sklearn.cross_validation import KFold
   5 from sklearn import neighbors
   6 from sklearn.datasets import load_iris
   7
   8 irisData = load_iris()
   9 X = irisData.data
  10 Y = irisData.target
  11
  12 kf = KFold(len(X), n_folds=10, shuffle=True)
  13
  14 scores = []
  15 for k in range(1, 30):
  16     score = 0
  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)
  25     scores.append(score)
  26
  27 print(scores)
  28 print("meilleure valeur pour k : ", scores.index(max(scores)) + 1)