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.
107 lines
3.4 KiB
C#
107 lines
3.4 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>
|
|
/// Normalized Kernel.
|
|
/// </summary>
|
|
///
|
|
/// <remarks>
|
|
/// This kernel definition can be used to provide normalized versions
|
|
/// of other kernel classes, such as the <see cref="Polynomial"/>. A
|
|
/// normalized kernel will always produce distances between -1 and 1.
|
|
/// </remarks>
|
|
///
|
|
[Serializable]
|
|
public sealed class Normalized<TKernel, TInput> : KernelBase<TInput>, IKernel<TInput>, ICloneable
|
|
where TKernel : IKernel<TInput>
|
|
{
|
|
private TKernel kernel;
|
|
private double power;
|
|
|
|
/// <summary>
|
|
/// Gets or sets the inner kernel function
|
|
/// whose results should be normalized.
|
|
/// </summary>
|
|
///
|
|
public TKernel Kernel
|
|
{
|
|
get { return kernel; }
|
|
set { kernel = value; }
|
|
}
|
|
|
|
/// <summary>
|
|
/// Gets or sets the normalization power to be
|
|
/// used. Default is 0.5 (take the square root).
|
|
/// </summary>
|
|
///
|
|
public double Power
|
|
{
|
|
get { return power; }
|
|
set { power = value; }
|
|
}
|
|
|
|
/// <summary>
|
|
/// Constructs a new Cauchy Kernel.
|
|
/// </summary>
|
|
///
|
|
/// <param name="kernel">The kernel function to be normalized.</param>
|
|
/// <param name="power">The normalization power to be used. Default is 0.5 (take the square root).</param>
|
|
///
|
|
public Normalized(TKernel kernel, double power = 0.5)
|
|
{
|
|
this.kernel = kernel;
|
|
this.power = power;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Normalized 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(TInput x, TInput y)
|
|
{
|
|
return kernel.Function(x, y) / Math.Pow(kernel.Function(x, x) * kernel.Function(y, y), power);
|
|
}
|
|
|
|
/// <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();
|
|
}
|
|
}
|
|
}
|