import numpy as np
import pandas as  pd
from sklearn import cross_validation, neighbors ,preprocessing

df = pd.read_csv('breast-cancer-wisconsin.data.txt')
df.replace('?', -99999,inplace=True)
df.drop(['id'],1,inplace=True)

X =  np.array(df.drop(['class'],1))
y = np.array(df['class'])

X_train, X_test , y_train , y_test = cross_validation.train_test_split(X,y, test_size = 0.2)

clf = neighbors.KNeighborsClassifier()
clf.fit(X_train,y_train)

accuracy = clf.score(X_test,y_test)
print(accuracy)

example_measure = np.array([ [4,2,1,1,1,2,3,2,1],[4,2,1,1,1,2,3,2,1] ])
example_measure = example_measure.reshape(len(example_measure),-1)

prediction = clf.predict(example_measure)
print(prediction)
