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 - if min >= 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 - if min >= max.

• function

  public static FeatureInitializer function(UnivariateFunction f,
                            double init,
                            double inc)

  Creates an initializer from a univariate function f(x). The argument x is set to init 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 return orig.value() + random.sample().