tf.contrib.factorization.GmmAlgorithm

Tensorflow Gaussian mixture model clustering class.

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

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assignments

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

clusters

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Returns the clusters with dimensions num_classes X 1 X num_dimensions.

covariances

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Returns the covariances matrices.

init_ops

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Returns the initialization operation.

is_initialized

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Returns a boolean operation for initialized variables.

log_likelihood_op

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Returns the log-likelihood operation.

scores

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Returns the per-sample likelihood fo the data.

Returns
Log probabilities of each data point.

training_ops

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Returns the training operation.

Class Variables

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

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/contrib/factorization/GmmAlgorithm