Uses of Class
de.jungblut.classification.nn.MultilayerPerceptronCostFunction.NetworkConfiguration

Packages that use MultilayerPerceptronCostFunction.NetworkConfiguration

Package	Description
de.jungblut.classification.nn

Uses of MultilayerPerceptronCostFunction.NetworkConfiguration in de.jungblut.classification.nn

Methods in de.jungblut.classification.nn with parameters of type MultilayerPerceptronCostFunction.NetworkConfiguration

Modifier and Type	Method	Description
static de.jungblut.math.DoubleMatrix[]	MultilayerPerceptronCostFunction.backwardPropagate(de.jungblut.math.DoubleMatrix y, de.jungblut.math.DoubleMatrix[] thetas, de.jungblut.math.DoubleMatrix[] ax, de.jungblut.math.DoubleMatrix[] zx, MultilayerPerceptronCostFunction.NetworkConfiguration conf)
static void	MultilayerPerceptronCostFunction.calculateGradients(de.jungblut.math.DoubleMatrix[] thetas, de.jungblut.math.DoubleMatrix[] thetaGradients, de.jungblut.math.DoubleMatrix[] ax, de.jungblut.math.DoubleMatrix[] deltaX, int m, MultilayerPerceptronCostFunction.NetworkConfiguration conf)
static double	MultilayerPerceptronCostFunction.calculateRegularization(de.jungblut.math.DoubleMatrix[] thetas, int m, MultilayerPerceptronCostFunction.NetworkConfiguration conf)
static CostGradientTuple	MultilayerPerceptronCostFunction.computeNextStep(de.jungblut.math.DoubleVector input, de.jungblut.math.DoubleMatrix x, de.jungblut.math.DoubleMatrix y, MultilayerPerceptronCostFunction.NetworkConfiguration conf)	Do a full forward pass and backpropagate the error.
static void	MultilayerPerceptronCostFunction.dropoutVisibleLayer(de.jungblut.math.DoubleMatrix x, de.jungblut.math.DoubleMatrix[] ax, MultilayerPerceptronCostFunction.NetworkConfiguration conf)
static void	MultilayerPerceptronCostFunction.forwardPropagate(de.jungblut.math.DoubleMatrix[] thetas, de.jungblut.math.DoubleMatrix[] ax, de.jungblut.math.DoubleMatrix[] zx, MultilayerPerceptronCostFunction.NetworkConfiguration conf)