import sklearn
from sklearn import datasets
from sklearn import svm 
from sklearn import metrics
from sklearn.neighbors import KNeighborsClassifier

cancer = datasets.load_breast_cancer()

# print(cancer.feature_names)
# print(cancer.target_names)

x = cancer.data
y= cancer.target

x_train,x_test,y_train,y_test = sklearn.model_selection.train_test_split(x,y, test_size=0.2)

# print(x_train,y_train)

classes = ['malignant','benign']

clf = svm.SVC(kernel="linear",C=8)
clf.fit(x_train,y_train)

y_pred = clf.predict(x_test)

acc = metrics.accuracy_score(y_test,y_pred)

clf_2 = KNeighborsClassifier(n_neighbors=9)
clf_2.fit(x_train,y_train)
y_pred_2 = clf_2.predict(x_test)
acc_2 = metrics.accuracy_score(y_test,y_pred_2)

print("SVM method: ",acc)
print("KNeighbors method: ",acc_2)
