机器学习及优化算法可视化界面工具

<?xml version="1.0"?> <doc> <assembly> <name>Accord.Math</name> </assembly> <members> <member name="T:Accord.MachineLearning.ParallelLearningBase"> <summary> Base class for parallel learning algorithms. </summary> </member> <member name="P:Accord.MachineLearning.ParallelLearningBase.ParallelOptions"> <summary> Gets or sets the parallelization options for this algorithm. </summary> </member> <member name="P:Accord.MachineLearning.ParallelLearningBase.Token"> <summary> Gets or sets a cancellation token that can be used to cancel the algorithm while it is running. </summary> </member> <member name="M:Accord.MachineLearning.ParallelLearningBase.#ctor"> <summary> Initializes a new instance of the <see cref="T:Accord.MachineLearning.ParallelLearningBase"/> class. </summary> </member> <member name="M:Accord.MachineLearning.ParallelLearningBase.OnDeserializedMethod(System.Runtime.Serialization.StreamingContext)"> <summary> Called when the object is being deserialized. </summary> </member> <member name="T:Accord.Statistics.Classes"> <summary> Methods for operating with categorical data. </summary> </member> <member name="M:Accord.Statistics.Classes.GetRatio(System.Int32[],System.Int32[])"> <summary> Calculates the prevalence of a class for each variable. </summary> <param name="positives">An array of counts detailing the occurrence of the first class.</param> <param name="negatives">An array of counts detailing the occurrence of the second class.</param> <returns>An array containing the proportion of the first class over the total of occurrences.</returns> </member> <member name="M:Accord.Statistics.Classes.GetRatio(System.Int32[][],System.Int32,System.Int32)"> <summary> Calculates the prevalence of a class. </summary> <param name="data">A matrix containing counted, grouped data.</param> <param name="positiveColumn">The index for the column which contains counts for occurrence of the first class.</param> <param name="negativeColumn">The index for the column which contains counts for occurrence of the second class.</param> <returns>An array containing the proportion of the first class over the total of occurrences.</returns> </member> <member name="M:Accord.Statistics.Classes.Summarize(System.Int32[][],System.Int32,System.Int32)"> <summary> Groups the occurrences contained in data matrix of binary (dichotomous) data. This operation can be reversed using the <see cref="M:Accord.Statistics.Classes.Expand(System.Int32[][],System.Int32,System.Int32,System.Int32)"/> method. </summary> <param name="data">A data matrix containing at least a column of binary data.</param> <param name="groupIndex">Index of the column which contains the group label name.</param> <param name="yesNoIndex">Index of the column which contains the binary [0,1] data.</param> <returns> A matrix containing the group label in the first column, the number of occurrences of the first class in the second column and the number of occurrences of the second class in the third column. </returns> </member> <member name="M:Accord.Statistics.Classes.Separate``1(``0[],System.Int32[])"> <summary> Divides values into groups given a vector containing the group labels for every value. </summary> <typeparam name="T">The type of the values.</typeparam> <param name="values">The values to be separated into groups.</param> <param name="labels"> A vector containing the class label associated with each of the values. The labels must begin on 0 and its maximum value should be the number of groups - 1.</param> <returns>The original values divided into groups.</returns> <example> <code source="Unit Tests\Accord.Tests.Statistics\ClassesTest.cs" region="doc_random" /> </example> </member> <member name="M:Accord.Statistics.Classes.Separate``1(``0[],System.Int32[],System.Int32)"> <summary> Divides values into groups given a vector containing the group labels for every value. </summary> <typeparam name="T">The type of the values.</typeparam> <param name="values">The values to be separated into groups.</param> <param name="labels"> A vector containing the class label associated with each of the values. The labels must begin on 0 and its maximum value should be the number of groups - 1.</param> <param name="groups">The number of groups.</param> <returns>The original values divided into groups.</returns> <example> <code source="Unit Tests\Accord.Tests.Statistics\ClassesTest.cs" region="doc_random" /> </example> </member> <member name="M:Accord.Statistics.Classes.Expand(System.Int32[],System.Int32[],System.Int32[])"> <summary> Extends a grouped data into a full observation matrix. </summary> <param name="data">The group labels.</param> <param name="positives"> An array containing he occurrence of the positive class for each of the groups.</param> <param name="negatives"> An array containing he occurrence of the negative class for each of the groups.</param> <returns>A full sized observation matrix.</returns> </member> <member name="M:Accord.Statistics.Classes.Expand(System.Int32[][],System.Int32,System.Int32,System.Int32)"> <summary> Expands a grouped data into a full observation matrix. </summary> <param name="data">The grouped data matrix.</param> <param name="labelColumn">Index of the column which contains the labels in the grouped data matrix. </param> <param name="positiveColumn">Index of the column which contains the occurrences for the first class.</param> <param name="negativeColumn">Index of the column which contains the occurrences for the second class.</param> <returns>A full sized observation matrix.</returns> </member> <member name="M:Accord.Statistics.Classes.Random(System.Int32,System.Int32)"> <summary> Returns a random group assignment for a sample. </summary> <param name="samples">The sample size.</param> <param name="classes">The number of groups.</param> <example> <code source="Unit Tests\Accord.Tests.Statistics\ClassesTest.cs" region="doc_random" /> </example>