Files
jube-fork/Accord.MachineLearning/Rules/AssociationRule.cs
richard-churchman cc0a2bee21 Extensive modifications to the serialisation of Neural Network models to support Newtonsoft Json.net rather than Binary Serializer.
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.
2023-12-24 10:22:22 +01:00

114 lines
3.8 KiB
C#

// TODO: Implement the Apriori algorithm.
// Accord Machine Learning 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.MachineLearning.Rules
{
using Accord.Math;
using System;
using System.Linq;
using System.Text;
using Accord.Compat;
using System.Collections.Generic;
/// <summary>
/// Association rule.
/// </summary>
///
/// <typeparam name="T">The item type.</typeparam>
///
[Serializable]
public class AssociationRule<T>
{
/// <summary>
/// Gets or sets the set of items that triggers the
/// activation of this association rule.
/// </summary>
///
public SortedSet<T> X { get; set; }
/// <summary>
/// Gets or sets the set of items that are also likely to
/// be included in the original list given that <see cref="X">
/// the input items</see> are present.
/// </summary>
///
public SortedSet<T> Y { get; set; }
/// <summary>
/// Gets or sets the number of cases that support this rule
/// (the number of times this association has been seen in the
/// training set).
/// </summary>
///
public double Support { get; set; }
/// <summary>
/// Gets or sets the confidence of this rule (as a percentage).
/// </summary>
///
public double Confidence { get; set; }
/// <summary>
/// Determines whether this rule can be applied to a given input.
/// </summary>
/// <param name="input">The set of elements (being bought, or processed).</param>
///
/// <returns>True, if this rule can be applied to the given set of inputs; false othersie.</returns>
///
public bool Matches(SortedSet<T> input)
{
return X.IsSubsetOf(input);
}
/// <summary>
/// Determines whether this rule can be applied to a given input.
/// </summary>
/// <param name="input">The set of elements (being bought, or processed).</param>
///
/// <returns>True, if this rule can be applied to the given set of inputs; false othersie.</returns>
///
public bool Matches(T[] input)
{
return X.IsSubsetOf(input);
}
/// <summary>
/// Returns a <see cref="System.String" /> that represents this instance.
/// </summary>
/// <returns>
/// A <see cref="System.String" /> that represents this instance.
/// </returns>
public override string ToString()
{
var sb = new StringBuilder();
sb.Append(X.ToArray().ToString(OctaveArrayFormatProvider.InvariantCulture));
sb.Append(" -> ");
sb.Append(Y.ToArray().ToString(OctaveArrayFormatProvider.InvariantCulture));
sb.AppendFormat("; support: {0}, confidence: {1}", Support, Confidence);
return sb.ToString();
}
}
}