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Tensorflow Gaussian mixture model clustering class.
__init__( data, num_classes, initial_means=None, params='wmc', covariance_type=FULL_COVARIANCE, random_seed=0 )
data: a list of Tensors with data, each row is a new example.
num_classes: number of clusters.
initial_means: a Tensor with a matrix of means. If None, means are computed by sampling randomly.
params: Controls which parameters are updated in the training process. Can contain any combination of "w" for weights, "m" for means, and "c" for covariances.
covariance_type: one of "full", "diag".
random_seed: Seed for PRNG used to initialize seeds.
Exception if covariance type is unknown.
Returns a list of Tensors with the matrix of assignments per shard.
Returns the clusters with dimensions num_classes X 1 X num_dimensions.
Returns the covariances matrices.
Returns the initialization operation.
Returns a boolean operation for initialized variables.
Returns the log-likelihood operation.
Returns the per-sample likelihood fo the data.
Log probabilities of each data point.
Returns the training operation.