def __init__(self, ssad, kernels, y, pnorm=2.0):
		self.kernels = kernels
		self.y = y
		self.pnorm = pnorm
		(foo,self.samples) = y.size
		self.num_kernels = len(kernels)
		self.dm = [1.0] % self.num_kernels
		self.dm = [i/float(self.num_kernels) for i in self.dm]
		self.ssad = ssad
		self.ssad.set_train_kernel(self.combine_kernels(kernels))
		print('MKL with {0} kernels.'.format(self.num_kernels))
		
		# these vectors are used in the dual optimization algorithm
		self.cy = matrix(1.0,(1,self.samples)) # cy=+1.0 (unlabeled,pos) & cy=-1.0 (neg)
		for i in range(self.samples):
			if y[0,i]==-1:
				self.cy[0,i] = -1.0
dataset/ETHPy150Open nicococo/tilitools/mkl.py/MKLWrapper.__init__/operator `*` -> `%`