def apply_updates(self, updates, gamma, C):
WARPDecomposition.apply_updates(self, updates, gamma, C)
self.apply_matrix_update(self.W, updates.dW, gamma, C)
def apply_updates(self,updates,gamma,C):
WARPDecomposition.apply_updates(self,updates,gamma,C)
self.apply_matrix_update(self.W,updates.dW,gamma,C)
def __init__(self, num_rows, num_cols, X, d):
WARPDecomposition.__init__(self, num_rows, num_cols, d)
# W holds latent factors for each item feature
self.W = d**-0.5 * np.random.random_sample((X.shape[1], d))
self.X = X
self.is_sparse = isinstance(X, scipy.sparse.csr_matrix)
def __init__(self,num_rows,num_cols,X,d):
WARPDecomposition.__init__(self,num_rows,num_cols,d)
# W holds latent factors for each item feature
self.W = d**-0.5*np.random.random_sample((X.shape[1],d))
self.X = X
self.is_sparse = isinstance(X,scipy.sparse.csr_matrix)
