pydbm.dbm.restrictedboltzmannmachines package¶

pydbm.dbm.restrictedboltzmannmachines.rt_rbm module¶

class pydbm.dbm.restrictedboltzmannmachines.rt_rbm.RTRBM

Reccurent temploral restricted boltzmann machine.

get_feature_points

Extract feature points from hidden layer.

Returns: np.ndarray of feature points.
get_reconstruct_error_arr

Extract reconstructed errors.

Retruns:
np.ndarray of reconstructed errors.
get_reconstructed_arr

Extract reconstructed points.

Returns: np.ndarray of reconstructed points.
inference

Inferencing.

Parameters: observed_data_arr – The np.ndarray of observed data points, which is a rank-3 array-like or sparse matrix of shape: (The number of samples, The length of cycle, The number of features) 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. If you do not want to execute the mini-batch training, the value of batch_size must be -1. And r_batch_size is also parameter to control the mini-batch training but is refered only in inference and reconstruction. If this value is more than 0, the inferencing is a kind of reccursive learning with the mini-batch training. batch_size – Batch size in learning. The np.ndarray of feature points.
learn

Learning.

Parameters: observed_data_arr – The np.ndarray of observed data points, which is a rank-3 array-like or sparse matrix of shape: (The number of samples, The length of cycle, The number of features) traning_count – Training counts. batch_size – Batch size.