Class FeatureInitializerFactory
- java.lang.Object
-
- org.apache.commons.math4.neuralnet.FeatureInitializerFactory
-
public final class FeatureInitializerFactory extends Object
Creates functions that will select the initial values of a neuron's features.- Since:
- 3.3
-
-
Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method Description static FeatureInitializerfunction(DoubleUnaryOperator f, double init, double inc)Creates an initializer from a univariate functionf(x).static FeatureInitializerrandomize(org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler random, FeatureInitializer orig)Adds some amount of random data to the given initializer.static FeatureInitializeruniform(org.apache.commons.rng.UniformRandomProvider rng, double min, double max)Uniform sampling of the given range.
-
-
-
Method Detail
-
uniform
public static FeatureInitializer uniform(org.apache.commons.rng.UniformRandomProvider rng, double min, double max)
Uniform sampling of the given range.- Parameters:
min- Lower bound of the range.max- Upper bound of the range.rng- Random number generator used to draw samples from a uniform distribution.- Returns:
- an initializer such that the features will be initialized with values within the given range.
- Throws:
IllegalArgumentException- ifmin >= max.
-
function
public static FeatureInitializer function(DoubleUnaryOperator f, double init, double inc)
Creates an initializer from a univariate functionf(x). The argumentxis set toinitat the first call and will be incremented at each call.- Parameters:
f- Function.init- Initial value.inc- Increment- Returns:
- the initializer.
-
randomize
public static FeatureInitializer randomize(org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler random, FeatureInitializer orig)
Adds some amount of random data to the given initializer.- Parameters:
random- Random variable distribution sampler.orig- Original initializer.- Returns:
- an initializer whose
valuemethod will returnorig.value() + random.sample().
-
-