Package org.neuroph.util.random

Provides weights randomization techniques

See: Description

Class Summary

Class	Description
DistortRandomizer	This class provides distort randomization technique, which distorts existing weight values using specified distortion factor.
GaussianRandomizer	This class provides Gaussian randomization technique using Box Muller method.
HeZhangRenSunUniformWeightsRandomizer	Sources: https://arxiv.org/abs/1502.01852 Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification https://stats.stackexchange.com/questions/47590/what-are-good-initial-weights-in-a-neural-network https://github.com/keras-team/keras/blob/master/keras/initializers.py
NguyenWidrowRandomizer	This class provides NguyenWidrow randmization technique, which gives very good results for Multi Layer Perceptrons trained with back propagation family of learning rules.
RangeRandomizer	This class provides ranged weights randomizer, which randomize weights in specified [min, max] range.
WeightsRandomizer	Basic weights randomizer, iterates and randomizes all connection weights in network.

Package org.neuroph.util.random Description

Provides weights randomization techniques