예제 #1
0
 def __init__(self,
              Y,
              input_dim,
              X=None,
              kernel=None,
              init='PCA',
              num_inducing=10):
     if X is None:
         from ..util.initialization import initialize_latent
         X, fracs = initialize_latent(init, input_dim, Y)
     SparseGPRegression.__init__(self,
                                 X,
                                 Y,
                                 kernel=kernel,
                                 num_inducing=num_inducing)
예제 #2
0
 def __init__(self, Y, input_dim, kernel=None, init='PCA', num_inducing=10):
     X = self.initialise_latent(init, input_dim, Y)
     SparseGPRegression.__init__(self, X, Y, kernel=kernel, num_inducing=num_inducing)
예제 #3
0
 def __init__(self, Y, input_dim, X=None, kernel=None, init='PCA', num_inducing=10):
     if X is None:
         from ..util.initialization import initialize_latent
         X, fracs = initialize_latent(init, input_dim, Y)
     SparseGPRegression.__init__(self, X, Y, kernel=kernel, num_inducing=num_inducing)
예제 #4
0
파일: sparse_gplvm.py 프로젝트: jaidevd/GPy 
 def __init__(self, Y, input_dim, kernel=None, init='PCA', num_inducing=10):
     X = self.initialise_latent(init, input_dim, Y)
     SparseGPRegression.__init__(self, X, Y, kernel=kernel, num_inducing=num_inducing)
     self.ensure_default_constraints()