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|
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
alphas()
assignments
assignments()
Returns a list of Tensors with the matrix of assignments per shard.
clusters
clusters()
Returns the clusters with dimensions num_classes X 1 X num_dimensions.
covariances
covariances()
Returns the covariances matrices.
init_ops
init_ops()
Returns the initialization operation.
is_initialized
is_initialized()
Returns a boolean operation for initialized variables.
log_likelihood_op
log_likelihood_op()
Returns the log-likelihood operation.
scores
scores()
Returns the per-sample likelihood fo the data.
| Returns | |
|---|---|
| Log probabilities of each data point. |
training_ops
training_ops()
Returns the training operation.