<commit_before>package tv.floe.metronome.deeplearning.dbn;

import java.util.ArrayList;

import org.apache.commons.math3.random.MersenneTwister;
import org.apache.mahout.math.Matrix;
import org.apache.mahout.math.Vector;
import org.apache.commons.math3.random.MersenneTwister;
import org.apache.commons.math3.random.RandomGenerator;

import tv.floe.metronome.classification.neuralnetworks.core.Layer;
import tv.floe.metronome.classification.neuralnetworks.networks.MultiLayerPerceptronNetwork;
import tv.floe.metronome.deeplearning.rbm.RestrictedBoltzmannMachine;
import tv.floe.metronome.math.MatrixUtils;

/**
 * Base draft of a Deep Belief Network based on RBMs
 * (based on concepts by Hinton)
 * 
 *  1. Setup as a normal MLPN 
 *  - but it also has a set of RBM layers that matches the number of hidden layers
 *  
 *  2. as each RBM is trained<commit_msg>added DBN resource for lit review in docs<commit_after>package tv.floe.metronome.deeplearning.dbn;

import java.util.ArrayList;

import org.apache.commons.math3.random.MersenneTwister;
import org.apache.mahout.math.Matrix;
import org.apache.mahout.math.Vector;
import org.apache.commons.math3.random.MersenneTwister;
import org.apache.commons.math3.random.RandomGenerator;

import tv.floe.metronome.classification.neuralnetworks.core.Layer;
import tv.floe.metronome.classification.neuralnetworks.networks.MultiLayerPerceptronNetwork;
import tv.floe.metronome.deeplearning.rbm.RestrictedBoltzmannMachine;
import tv.floe.metronome.math.MatrixUtils;

/**
 * Base draft of a Deep Belief Network based on RBMs
 * (based on concepts by Hinton)
 * 
 * Literature Review and Notes
 * 
 * 1. http://www.iro.umontreal.ca/~lisa/twiki/bin/view.cgi/Public/DBNPseudoCode
 * 
 * 
 *  1. Setup as a normal MLPN 
 *  - but it also has a set of RBM layers that matches the number of hidden layers
 *  
 *  2. as each RBM is trained
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{'dir': 'git-commits-cleaned', 'id': '4443047', 'n_tokens_mistral': 646, 'n_tokens_neox': 621, 'n_words': 142}