Defines the interface for a class that is capable of randomizing the weights and bias values of a neural network.
Provides basic functionality that most randomizers will need.
A randomizer that takes a seed and will always produce consistent results.
A randomizer that will create always set the random number to a const value, used mainly for testing.
A randomizer that distorts what is already present in the neural network.
A randomizer that attempts to create starting weight values that are conducive to propagation training.
Generally, you will not want to use this randomizer as a pure neural network randomizer.
Implementation of Nguyen-Widrow weight initialization.
Generate random choices unevenly.
A randomizer that will create random weight and bias values that are between a specified range.
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