mdl = SVC(C=c,kernel='rbf',degree=1,tol=0.0001)
mdl = rfc(n_estimators=100,criterion='entropy',min_samples_leaf=5,min_samples_split=10,max_features=8)
mdl = knn(n_neighbors=nb)
mdl.fit(td,tc)
for i in range(dtsize):
td_index = []
for k in range(repl_fact):
td_index.append( dtsize*k + i)
tsd_1 = np.array(tsd[td_index,:])
tst_class_act=test_class[i]
ab = mdl.kneighbors(tsd_1,return_distance=True)
pos = ab[1]
outcome = np.ravel(tc[pos])
''' 1
print ab
print
print pos
print
print outcome
print
'''
tst_class_pred_df = pd.DataFrame(outcome)
#print tst_class_pred
try:
