A sigmoid kernel function for a linear classifier to adapt it to data that is not linearly separable. More...

#include <sigmoid.h>

Public Member Functions
	sigmoid (double alpha, double c)
	Constructs a new sigmoid kernel with the given parameters. More...

template<class PostingsData >
double	operator() (const PostingsData &first, const PostingsData &second) const
	Computes the value of \(K(first, second)\).

Private Attributes
double	alpha_
	\(\alpha\), the coefficient for the dot product.

double	c_
	\(c\), the additional scalar term

polynomial	dot_ {1, 0.0}
	Internal "helper" kernel.

Detailed Description

A sigmoid kernel function for a linear classifier to adapt it to data that is not linearly separable.

Uses the general form of: \(K(x,y) = \tanh(\alpha x^T y + c)\)

Constructor & Destructor Documentation

meta::classify::kernel::sigmoid::sigmoid	(	double	alpha,
		double	c
	)

inline

Constructs a new sigmoid kernel with the given parameters.

Parameters

alpha	\(\alpha\), the coefficient for the dot product
c	\(c\), the additional scalar term

The documentation for this class was generated from the following files: