# pydbm.approximation.interface package¶

## pydbm.approximation.interface.approximate_interface module¶

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. 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) Graph of neurons.
reconstruct_error_list

Reconstruction error.