pydbm.approximation.interface package¶

Submodules¶

class pydbm.approximation.interface.approximate_interface.ApproximateInterface¶

Bases: object

The interface for function approximations.

approximate_inference¶

Inference with function approximation.

Parameters:

graph – Graph of neurons.
learning_rate – Learning rate.
learning_attenuate_rate – Attenuate the learning_rate by a factor of this value every attenuate_epoch.
attenuate_epoch – Attenuate the learning_rate by a factor of learning_attenuate_rate every attenuate_epoch.
dropout_rate – Dropout rate.
observed_data_arr – Observed data points.
training_count – Training counts.
r_batch_size – Batch size. If this value is 0, the inferencing is a recursive learning. If this value is more than 0, the inferencing is a mini-batch recursive learning. If this value is ‘-1’, the inferencing is not a recursive learning.

Returns:

Graph of neurons.

approximate_learn¶

learning with function approximation.

Parameters:

graph – Graph of neurons.
learning_rate – Learning rate.
learning_attenuate_rate – Attenuate the learning_rate by a factor of this value every attenuate_epoch.
attenuate_epoch – Attenuate the learning_rate by a factor of learning_attenuate_rate every attenuate_epoch.
dropout_rate – Dropout rate.
observed_data_arr – Observed data points.
training_count – Training counts.
batch_size – Batch size (0: not mini-batch)

Returns:

Graph of neurons.