Class FeatureInitializerFactory
- java.lang.Object
-
- org.apache.commons.math3.ml.neuralnet.FeatureInitializerFactory
-
public class FeatureInitializerFactory extends java.lang.Object
Creates functions that will select the initial values of a neuron's features.- Since:
- 3.3
-
-
Constructor Summary
Constructors Modifier Constructor Description private
FeatureInitializerFactory()
Class contains only static methods.
-
Method Summary
All Methods Static Methods Concrete Methods Modifier and Type Method Description static FeatureInitializer
function(UnivariateFunction f, double init, double inc)
Creates an initializer from a univariate functionf(x)
.static FeatureInitializer
randomize(RealDistribution random, FeatureInitializer orig)
Adds some amount of random data to the given initializer.static FeatureInitializer
uniform(double min, double max)
Uniform sampling of the given range.static FeatureInitializer
uniform(RandomGenerator rng, double min, double max)
Uniform sampling of the given range.
-
-
-
Method Detail
-
uniform
public static FeatureInitializer uniform(RandomGenerator 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:
NumberIsTooLargeException
- ifmin >= max
.
-
uniform
public static FeatureInitializer uniform(double min, double max)
Uniform sampling of the given range.- Parameters:
min
- Lower bound of the range.max
- Upper bound of the range.- Returns:
- an initializer such that the features will be initialized with values within the given range.
- Throws:
NumberIsTooLargeException
- ifmin >= max
.
-
function
public static FeatureInitializer function(UnivariateFunction f, double init, double inc)
Creates an initializer from a univariate functionf(x)
. The argumentx
is set toinit
at 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(RealDistribution random, FeatureInitializer orig)
Adds some amount of random data to the given initializer.- Parameters:
random
- Random variable distribution.orig
- Original initializer.- Returns:
- an initializer whose
value
method will returnorig.value() + random.sample()
.
-
-