def test_CNN(x, y):
print('Condensed Nearest Neighbour')
CNN = CondensedNearestNeighbour(verbose=verbose)
cnnx, cnny = CNN.fit_transform(x, y)
print('One-Sided Selection')
OSS = OneSidedSelection(verbose=verbose)
ossx, ossy = OSS.fit_transform(x, y)
print('BalanceCascade')
BS = BalanceCascade(verbose=verbose)
bsx, bsy = BS.fit_transform(x, y)
def test_CNN(x, y):
print('Condensed Nearest Neighbour')
CNN = CondensedNearestNeighbour(verbose=verbose)
cnnx, cnny = CNN.fit_transform(x, y)
print('One-Sided Selection')
OSS = OneSidedSelection(verbose=verbose)
ossx, ossy = OSS.fit_transform(x, y)
print('BalanceCascade')
BS = BalanceCascade(verbose=verbose)
bsx, bsy = BS.fit_transform(x, y)
def balance_data_ensemblesampling_balance_cascade(self):
'''
Balance data using balance cascade.
'''
x = self.X
y = self.y
y.shape = (len(self.y))
verbose = True
BS = BalanceCascade(verbose=verbose)
bsx, bsy = BS.fit_transform(x, y)
self.X = bsx
self.y = bsy
self.y.shape = (len(self.y), 1)
def test_CNN(x, y):
print('Condensed Nearest Neighbour')
CNN = CondensedNearestNeighbour(indices_support=indices_support, verbose=verbose)
cnnx, cnny, idx_tmp = CNN.fit_transform(x, y)
print ('Indices selected')
print(idx_tmp)
print('One-Sided Selection')
OSS = OneSidedSelection(indices_support=indices_support, verbose=verbose)
ossx, ossy, idx_tmp = OSS.fit_transform(x, y)
print ('Indices selected')
print(idx_tmp)
print('BalanceCascade')
BS = BalanceCascade(verbose=verbose)
bsx, bsy = BS.fit_transform(x, y)
def test_CNN(x, y,c=0,ratio='auto'):
if(c==0):
print('Condensed Nearest Neighbour')
CNN = CondensedNearestNeighbour(indices_support=indices_support, verbose=verbose)
x,y, idx_tmp = CNN.fit_transform(x, y)
print ('Indices selected')
print(idx_tmp)
elif(c==1):
print('One-Sided Selection')
OSS = OneSidedSelection(indices_support=indices_support, verbose=verbose)
x,y, idx_tmp = OSS.fit_transform(x, y)
print ('Indices selected')
print(idx_tmp)
elif(c==2):
print('BalanceCascade')
BS = BalanceCascade(ratio='auto',verbose=verbose)
x,y = BS.fit_transform(x, y)
return x,y
