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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.
62 lines
2.2 KiB
C#
62 lines
2.2 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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namespace Accord.Statistics.Models.Markov
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{
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using System;
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/// <summary>
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/// Common interface for sequence classifiers using <see cref="IHiddenMarkovModel">
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/// hidden Markov models</see>.
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/// </summary>
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///
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[Obsolete("Please use IMulticlassClassifier from Accord.MachineLearning namespace.")]
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public interface IHiddenMarkovClassifier
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{
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/// <summary>
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/// Computes the most likely class for a given sequence.
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/// </summary>
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///
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/// <param name="sequence">The sequence of observations.</param>
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/// <param name="responsibilities">The class responsibilities (or
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/// the probability of the sequence to belong to each class). When
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/// using threshold models, the sum of the probabilities will not
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/// equal one, and the amount left was the threshold probability.
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/// If a threshold model is not being used, the array should sum to
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/// one.</param>
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///
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/// <returns>Return the label of the given sequence, or -1 if it has
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/// been rejected.</returns>
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///
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int Compute(Array sequence, out double[] responsibilities);
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/// <summary>
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/// Gets the number of classes which can be recognized by this classifier.
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/// </summary>
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///
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int Classes { get; }
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}
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}
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