tf.contrib.factorization.GmmAlgorithm

Tensorflow Gaussian mixture model clustering class.

tf.contrib.factorization.GmmAlgorithm(
    data, num_classes, initial_means=None, params='wmc',
    covariance_type=FULL_COVARIANCE, random_seed=0
)

Args
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.

Raises
Exception if covariance type is unknown.

Methods

alphas

View source

alphas()

assignments

View source

assignments()

Returns a list of Tensors with the matrix of assignments per shard.

clusters

View source

clusters()

Returns the clusters with dimensions num_classes X 1 X num_dimensions.

covariances

View source

covariances()

Returns the covariances matrices.

init_ops

View source

init_ops()

Returns the initialization operation.

is_initialized

View source

is_initialized()

Returns a boolean operation for initialized variables.

log_likelihood_op

View source

log_likelihood_op()

Returns the log-likelihood operation.

scores

View source

scores()

Returns the per-sample likelihood fo the data.

Returns
Log probabilities of each data point.

training_ops

View source

training_ops()

Returns the training operation.

Class Variables

• CLUSTERS_COVS_VARIABLE = 'clusters_covs'
• CLUSTERS_VARIABLE = 'clusters'
• CLUSTERS_WEIGHT = 'alphas'