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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.
128 lines
3.9 KiB
C#
128 lines
3.9 KiB
C#
// Accord Statistics Library
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// The Accord.NET Framework
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// http://accord-framework.net
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//
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// Copyright © César Souza, 2009-2017
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// cesarsouza at gmail.com
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//
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// This library is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 2.1 of the License, or (at your option) any later version.
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//
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// This library is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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// Lesser General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License along with this library; if not, write to the Free Software
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// Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
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//
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using System;
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namespace Accord.Statistics.Analysis
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{
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/// <summary>
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/// Determines the method to be used in a statistical analysis.
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/// </summary>
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///
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public enum AnalysisMethod
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{
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/// <summary>
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/// By choosing Center, the method will be run on the mean-centered data.
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/// </summary>
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///
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/// <remarks>
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/// In Principal Component Analysis this means the method will operate
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/// on the Covariance matrix of the given data.
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/// </remarks>
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///
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Center = 0,
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/// <summary>
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/// By choosing Standardize, the method will be run on the mean-centered and
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/// standardized data.
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/// </summary>
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///
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/// <remarks>
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/// In Principal Component Analysis this means the method
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/// will operate on the Correlation matrix of the given data. One should always
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/// choose to standardize when dealing with different units of variables.
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/// </remarks>
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///
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Standardize = 1,
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};
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/// <summary>
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/// Determines the method to be used in a statistical analysis.
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/// </summary>
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///
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public enum PrincipalComponentMethod
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{
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/// <summary>
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/// By choosing Center, the method will be run on the mean-centered data.
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/// </summary>
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///
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/// <remarks>
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/// In Principal Component Analysis this means the method will operate
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/// on the Covariance matrix of the given data.
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/// </remarks>
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///
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Center = 0,
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/// <summary>
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/// By choosing Standardize, the method will be run on the mean-centered and
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/// standardized data.
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/// </summary>
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///
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/// <remarks>
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/// In Principal Component Analysis this means the method
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/// will operate on the Correlation matrix of the given data. One should always
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/// choose to standardize when dealing with different units of variables.
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/// </remarks>
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///
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Standardize = 1,
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/// <summary>
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/// By choosing CorrelationMatrix, the method will interpret the given data
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/// as a correlation matrix.
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/// </summary>
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///
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CorrelationMatrix = 2,
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/// <summary>
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/// By choosing CovarianceMatrix, the method will interpret the given data
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/// as a correlation matrix.
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/// </summary>
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///
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CovarianceMatrix = 3,
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/// <summary>
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/// By choosing KernelMatrix, the method will interpret the given data
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/// as a Kernel (Gram) matrix.
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/// </summary>
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///
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KernelMatrix = 4,
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};
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/// <summary>
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/// Common interface for statistical analysis.
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/// </summary>
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///
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[Obsolete]
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public interface IAnalysis
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{
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/// <summary>
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/// Computes the analysis using given source data and parameters.
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/// </summary>
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///
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void Compute();
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}
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}
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