Class Summary |
BasicRandomizer |
Provides basic functionality that most randomizers will need. |
ConsistentRandomizer |
A randomizer that takes a seed and will always produce consistent results. |
ConstRandomizer |
A randomizer that will create always set the random number to a const value,
used mainly for testing. |
Distort |
A randomizer that distorts what is already present in the neural network. |
FanInRandomizer |
A randomizer that attempts to create starting weight values that are
conducive to propagation training. |
GaussianRandomizer |
Generally, you will not want to use this randomizer as a pure neural network
randomizer. |
NguyenWidrowRandomizer |
Implementation of Nguyen-Widrow weight initialization. |
RandomChoice |
Generate random choices unevenly. |
RangeRandomizer |
A randomizer that will create random weight and bias values that are between
a specified range. |