import numpy as np
from sklearn_extra.cluster import KMedoids
from sklearn.svm import OneClassSVM

def featureSelection(x):
    return np.percentile(x, np.arange(10,100,10))

def MyFunc(t_end):
    print (t_end)
    kmedoids = KMedoids (n_clusters = 2, random_state = 0).fit(t_end)
    result = kmedoids.labels_
    print(result)
    return result
 
def SVM(X):
    clf = OneClassSVM(kernel = 'rbf', gamma=0.01, nu=0.4).fit(X)
    print(clf.predict(X))