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[TP_AA.git] / TP1 / exo2 / TP1prog3.py

#!/usr/bin/env python3

# -*- coding: utf-8 -*-
import random
from sklearn import neighbors
from sklearn.cross_validation import train_test_split
from sklearn.datasets import load_iris

irisData = load_iris()

X = irisData.data
Y = irisData.target

# print(help(train_test_split))
X_train, X_test, Y_train, Y_test = train_test_split(
    X, Y, test_size=0.3, random_state=random.seed())
# print(len(X_train))
# print(len(X_test))
# print(len(X_train[Y_train == 0]))
# print(len(X_train[Y_train == 1]))
# print(len(X_train[Y_train == 2]))

nb_voisins = 15
clf = neighbors.KNeighborsClassifier(nb_voisins)
clf.fit(X_train, Y_train)
# print("kNN prediction on [5.4, 3.2, 1.6, 0.4]:")
# print(clf.predict([[5.4, 3.2, 1.6, 0.4]]))
# print("kNN probability prediction on [5.4, 3.2, 1.6, 0.4]:")
# print(clf.predict_proba([[5.4, 3.2, 1.6, 0.4]]))
print("kNN score on Iris test data:")
print(clf.score(X_test, Y_test))
print("kNN prediction error(s) on Iris test data:")
Z = clf.predict(X_test)
print(X_test[Z != Y_test])