mirror of
https://github.com/hanzoai/jube-fork.git
synced 2026-10-30 18:33:33 +00:00
richard-churchman
cc0a2bee21
Included open-source Accord.net library code natively to the solution given the deprecated state of that project. Accord.net will be supported inside Jube for own needs (such as upgrading to .Net 7+). Accord.net libraries modified to compile to .Net 6. Modified Accord.net libraries to better support Newtonsoft Json.net serialisation. Included annotations in the Accord.net libraries to house important dependency statistics. Serialised json can be used independently of Jube to recall a Neural Network. Removal of Binary Serializer totally as a precursor to the projects support of .Net 7+. Extensive bug fixing in crucial functions of Neural Network training and recall. While this part of the system remains in Alpha, it is substantially more fit for purpose.
134 lines
3.8 KiB
C#
134 lines
3.8 KiB
C#
// Accord Statistics Library
|
|
// The Accord.NET Framework
|
|
// http://accord-framework.net
|
|
//
|
|
// Copyright © César Souza, 2009-2017
|
|
// cesarsouza at gmail.com
|
|
//
|
|
// This library is free software; you can redistribute it and/or
|
|
// modify it under the terms of the GNU Lesser General Public
|
|
// License as published by the Free Software Foundation; either
|
|
// version 2.1 of the License, or (at your option) any later version.
|
|
//
|
|
// This library is distributed in the hope that it will be useful,
|
|
// but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
|
|
// Lesser General Public License for more details.
|
|
//
|
|
// You should have received a copy of the GNU Lesser General Public
|
|
// License along with this library; if not, write to the Free Software
|
|
// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
|
|
//
|
|
|
|
namespace Accord.Statistics.Kernels
|
|
{
|
|
using System;
|
|
using Accord.Compat;
|
|
|
|
/// <summary>
|
|
/// Bessel Kernel.
|
|
/// </summary>
|
|
///
|
|
/// <remarks>
|
|
/// The Bessel kernel is well known in the theory of function spaces
|
|
/// of fractional smoothness.
|
|
/// </remarks>
|
|
///
|
|
[Serializable]
|
|
public sealed class Bessel : KernelBase, IKernel,
|
|
IRadialBasisKernel, ICloneable
|
|
{
|
|
private int order;
|
|
private double sigma;
|
|
|
|
/// <summary>
|
|
/// Gets or sets the order of the Bessel function.
|
|
/// </summary>
|
|
///
|
|
public int Order
|
|
{
|
|
get { return order; }
|
|
set { order = value; }
|
|
}
|
|
|
|
/// <summary>
|
|
/// Gets or sets the sigma constant for this kernel.
|
|
/// </summary>
|
|
///
|
|
public double Sigma
|
|
{
|
|
get { return sigma; }
|
|
set { sigma = value; }
|
|
}
|
|
|
|
/// <summary>
|
|
/// Constructs a new Bessel Kernel.
|
|
/// </summary>
|
|
///
|
|
/// <param name="order">The order for the Bessel function.</param>
|
|
/// <param name="sigma">The value for sigma.</param>
|
|
///
|
|
public Bessel(int order, double sigma)
|
|
{
|
|
this.order = order;
|
|
this.sigma = sigma;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Bessel Kernel Function
|
|
/// </summary>
|
|
///
|
|
/// <param name="x">Vector <c>x</c> in input space.</param>
|
|
/// <param name="y">Vector <c>y</c> in input space.</param>
|
|
/// <returns>Dot product in feature (kernel) space.</returns>
|
|
///
|
|
public override double Function(double[] x, double[] y)
|
|
{
|
|
double norm = 0.0;
|
|
|
|
for (int k = 0; k < x.Length; k++)
|
|
{
|
|
double d = x[k] - y[k];
|
|
norm += d * d;
|
|
}
|
|
|
|
norm = System.Math.Sqrt(norm);
|
|
|
|
double num = Accord.Math.Bessel.J(order, sigma * norm);
|
|
double den = System.Math.Pow(norm, -norm * order);
|
|
|
|
return num / den;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Bessel Kernel Function
|
|
/// </summary>
|
|
///
|
|
/// <param name="z">Distance <c>z</c> between two vectors in input space.</param>
|
|
///
|
|
/// <returns>Dot product in feature (kernel) space.</returns>
|
|
///
|
|
public double Function(double z)
|
|
{
|
|
double num = Accord.Math.Bessel.J(order, sigma * z);
|
|
double den = System.Math.Pow(z, -z * order);
|
|
|
|
return num / den;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Creates a new object that is a copy of the current instance.
|
|
/// </summary>
|
|
///
|
|
/// <returns>
|
|
/// A new object that is a copy of this instance.
|
|
/// </returns>
|
|
///
|
|
public object Clone()
|
|
{
|
|
return MemberwiseClone();
|
|
}
|
|
|
|
}
|
|
}
|