rlab/plugin/neural/cdbn.js

Javascript scientific library like R

/**
 * Created by joonkukang on 2014. 1. 13..
 */
var NN = R.NN;

CDBN = module.exports = function (settings) {
    var self = this;
    self.x = settings['input'];
    self.y = settings['label'];
    self.sigmoidLayers = [];
    self.rbmLayers = [];
    self.nLayers = settings['hiddenLayerSizes'].length;
    self.hiddenLayerSizes = settings['hiddenLayerSizes'];
    self.nIns = settings['nIns'];
    self.nOuts = settings['nOuts'];

    self.settings = {
        'log level' : 1 // 0 : nothing, 1 : info, 2: warn
    };
    // Constructing Deep Neural Network
    var i;
    for(i=0 ; i<self.nLayers ; i++) {
        var inputSize, layerInput;
        if(i == 0)
            inputSize = settings['nIns'];
        else
            inputSize = settings['hiddenLayerSizes'][i-1];

        if(i == 0)
            layerInput = self.x;
        else
            layerInput = self.sigmoidLayers[self.sigmoidLayers.length-1].sampleHgivenV();

        var sigmoidLayer = new NN.HiddenLayer({
            input : layerInput,
            nIn : inputSize,
            nOut : settings['hiddenLayerSizes'][i],
            activation : NN.sigmoid
        });
        self.sigmoidLayers.push(sigmoidLayer);

        var rbmLayer;
        if(i==0) {
            rbmLayer = new NN.CRBM({
                input : layerInput,
                nVisible : inputSize,
                nHidden : settings['hiddenLayerSizes'][i],
            });
        } else {
            rbmLayer = new NN.RBM({
                input   : layerInput,
                nVisible: inputSize,
                nHidden : settings['hiddenLayerSizes'][i]
            });
        }
        self.rbmLayers.push(rbmLayer);
    }
    self.outputLayer = new NN.HiddenLayer({
        input: self.sigmoidLayers[self.sigmoidLayers.length-1].sampleHgivenV(),
        nIn  : settings['hiddenLayerSizes'][settings['hiddenLayerSizes'].length - 1],
        nOut : settings['nOuts'],
        activation : NN.sigmoid
    });
};

CDBN.prototype.__proto__ = DBN.prototype;