TP1/exo2/TP1prog3.py

   1 #!/usr/bin/env python3
   2
   3 # -*- coding: utf-8 -*-
   4 import random
   5 from sklearn import neighbors
   6 from sklearn.cross_validation import train_test_split
   7 from sklearn.datasets import load_iris
   8 irisData = load_iris()
   9
  10 X = irisData.data
  11 Y = irisData.target
  12
  13 # print(help(train_test_split))
  14 X_train, X_test, Y_train, Y_test = train_test_split(
  15     X, Y, test_size=0.3, random_state=random.seed())
  16 # print(len(X_train))
  17 # print(len(X_test))
  18 # print(len(X_train[Y_train == 0]))
  19 # print(len(X_train[Y_train == 1]))
  20 # print(len(X_train[Y_train == 2]))
  21
  22 nb_voisins = 15
  23 clf = neighbors.KNeighborsClassifier(nb_voisins)
  24 clf.fit(X_train, Y_train)
  25 # print("kNN prediction on [5.4, 3.2, 1.6, 0.4]:")
  26 # print(clf.predict([[5.4, 3.2, 1.6, 0.4]]))
  27 # print("kNN probability prediction on [5.4, 3.2, 1.6, 0.4]:")
  28 # print(clf.predict_proba([[5.4, 3.2, 1.6, 0.4]]))
  29 print("kNN score on Iris test data:")
  30 print(clf.score(X_test, Y_test))
  31 print("kNN prediction error(s) on Iris test data:")
  32 Z = clf.predict(X_test)
  33 print(X_test[Z != Y_test])