public BackPropNetwork(NetworkProperties props, BackPropProperties backProps, Random rnd)
        {
            this.rnd       = rnd; // for Shuffle()
            this.backProps = backProps;

            this.Network = new NeuralNetwork(props, rnd);

            // back-prop related arrays below
            this.hGrads = new double[props.NumHidden];
            this.oGrads = new double[props.NumOutput];

            this.ihPrevWeightsDelta = NetworkData.MakeMatrix(props.NumInput, props.NumHidden);
            this.hPrevBiasesDelta   = new double[props.NumHidden];
            this.hoPrevWeightsDelta = NetworkData.MakeMatrix(props.NumHidden, props.NumOutput);
            this.oPrevBiasesDelta   = new double[props.NumOutput];
        }
예제 #2
0
        public BackPropNetwork(NetworkProperties props, BackPropProperties backProps, Random rnd)
        {
            this.rnd = rnd; // for Shuffle()
            this.backProps = backProps;

            this.Network = new NeuralNetwork(props, rnd);

            // back-prop related arrays below
            this.hGrads = new double[props.NumHidden];
            this.oGrads = new double[props.NumOutput];

            this.ihPrevWeightsDelta = NetworkData.MakeMatrix(props.NumInput, props.NumHidden);
            this.hPrevBiasesDelta = new double[props.NumHidden];
            this.hoPrevWeightsDelta = NetworkData.MakeMatrix(props.NumHidden, props.NumOutput);
            this.oPrevBiasesDelta = new double[props.NumOutput];
        }
예제 #3
0
        static INeuralNetwork BuildBackPropNetwork()
        {
            var props = new NetworkProperties {
                InitWeightMin = -0.1,
                InitWeightMax = 0.1,
                NumHidden = Globals.gNumHidden,  // orig 2
                NumInput = Globals.gNumInput,    // orig 4
                NumOutput = Globals.gNumOutput   // orig 3
            };

            var backProps = new BackPropProperties
                                {
                                    learnRate = 0.05,
                                    maxEprochs = Globals.gMaxIterations, // orig 2000,
                                    momentum = 0.00,
                                    weightDecay = 0.000,
                                    mseStopCondition = 0.020
                                };

            return  new BackPropNetwork(props, backProps, new Random(0));
        }
예제 #4
0
        static INeuralNetwork BuildBackPropNetwork()
        {
            var props = new NetworkProperties {
                InitWeightMin = -0.1,
                InitWeightMax = 0.1,
                NumHidden = 2,
                NumInput = 4,
                NumOutput = 3
            };

            var backProps = new BackPropProperties
                                {
                                    learnRate = 0.05,
                                    maxEprochs = 2000,
                                    momentum = 0.00,
                                    weightDecay = 0.000,
                                    mseStopCondition = 0.020
                                };

            return  new BackPropNetwork(props, backProps, new Random(0));
        }