Base class for Discriminant Analysis (LDA, QDA or KDA).
Inheritance Hierarchy Namespace: Accord.Statistics.AnalysisAccord.Statistics (in Accord.Statistics.dll) Version: 3.8.0
Syntax[SerializableAttribute] public abstract class BaseDiscriminantAnalysis : TransformBase<double[], double[]>
<SerializableAttribute> Public MustInherit Class BaseDiscriminantAnalysis Inherits TransformBase(Of Double(), Double())Request Example View Source
The BaseDiscriminantAnalysis type exposes the following members.
Constructors Properties Name Description ClassCountGets the observation count for each class.
ClassesGets information about the distinct classes in the analyzed data.
Classifications Obsolete.Gets the original classifications (labels) of the source data given on the moment of creation of this analysis object.
ClassMeansGets the Mean vector for each class.
ClassScatterGets the Scatter matrix for each class.
ClassStandardDeviationsGets the Standard Deviation vector for each class.
CumulativeProportionsThe cumulative distribution of the discriminants factors proportions. Also known as the cumulative energy of the first dimensions of the discriminant space or as the amount of variance explained by those dimensions.
DiscriminantMatrix Obsolete.Gets the Eigenvectors obtained during the analysis, composing a basis for the discriminant factor space.
DiscriminantProportionsGets the level of importance each discriminant factor has in discriminant space. Also known as amount of variance explained.
DiscriminantsGets the discriminant factors in a object-oriented fashion.
DiscriminantVectorsGets the Eigenvectors obtained during the analysis, composing a basis for the discriminant factor space.
EigenvaluesGets the Eigenvalues found by the analysis associated with each vector of the ComponentMatrix matrix.
MeansGets the mean of the original data given at method construction.
NumberOfClassesGets the number of classes in the analysis.
NumberOfInputsGets the number of inputs accepted by the model.
(Inherited from TransformBaseTInput, TOutput.) NumberOfOutputsGets the number of outputs generated by the model.
(Inherited from TransformBaseTInput, TOutput.) NumberOfSamplesGets the number of samples used to create the analysis.
ProjectionMeansGets the feature space mean of the projected data.
Result Obsolete.Gets the resulting projection of the source data given on the creation of the analysis into discriminant space.
ScatterBetweenClassGets the Between-Class Scatter Matrix for the data.
ScatterMatrixGets the Total Scatter Matrix for the data.
ScatterWithinClassGets the Within-Class Scatter Matrix for the data.
Source Obsolete.Returns the original supplied data to be analyzed.
StandardDeviationsGets the standard mean of the original data given at method construction.
ThresholdGets or sets the minimum variance proportion needed to keep a discriminant component. If set to zero, all components will be kept. Default is 0.001 (all components which contribute less than 0.001 to the variance in the data will be discarded).
TokenGets or sets a cancellation token that can be used to stop the learning algorithm while it is running.
Top Methods Name Description Classify(Double) Obsolete.Classifies a new instance into one of the available classes.
Classify(Double) Obsolete.Classifies new instances into one of the available classes.
Classify(Double, Double) Obsolete.Classifies a new instance into one of the available classes.
CreateDiscriminantsCreates additional information about principal components.
DiscriminantFunctionGets the output of the discriminant function for a given class.
EqualsDetermines whether the specified object is equal to the current object.
(Inherited from Object.) FinalizeAllows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.) GetHashCodeServes as the default hash function.
(Inherited from Object.) GetNonzeroEigenvaluesReturns the number of discriminant space dimensions (discriminant factors) whose variance is greater than a given threshold.
GetNumberOfDimensionsReturns the minimum number of discriminant space dimensions (discriminant factors) required to represent a given percentile of the data.
GetTypeGets the Type of the current instance.
(Inherited from Object.) init Obsolete.Obsolete.
InitInitializes common properties.
MemberwiseCloneCreates a shallow copy of the current Object.
(Inherited from Object.) ToStringReturns a string that represents the current object.
(Inherited from Object.) Transform(Double) Obsolete.Obsolete.
Transform(Double)Applies the transformation to an input, producing an associated output.
(Overrides TransformBaseTInput, TOutputTransform(TInput).) Transform(Double)Applies the transformation to an input, producing an associated output.
(Overrides TransformBaseTInput, TOutputTransform(TInput).) Transform(TInput, TOutput)Applies the transformation to an input, producing an associated output.
(Inherited from TransformBaseTInput, TOutput.) Transform(Double, Int32) Obsolete.Obsolete.
Transform(Double, Int32) Obsolete.Obsolete.
Transform(Double, Int32) Obsolete.Obsolete.
Top Extension Methods Name Description HasMethodChecks whether an object implements a method with the given name.
(Defined by ExtensionMethods.) IsEqualCompares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.
(Defined by Matrix.) To(Type) Overloaded.Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) ToT Overloaded.Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) Top See AlsoRetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4