DiscretizationTInput, TOutputOptions Class

Options for the discretization filter.

Inheritance Hierarchy

SystemObject
Accord.Statistics.FiltersColumnOptionsBaseDiscretizationTInput, TOutput
Accord.Statistics.FiltersDiscretizationTInput, TOutputOptions

Namespace: Accord.Statistics.Filters
Assembly: Accord.Statistics (in Accord.Statistics.dll) Version: 3.8.0

Syntax

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[SerializableAttribute]
public class Options : ColumnOptionsBase<Discretization<TInput, TOutput>>, 
	ITransform<TInput, TOutput>, ICovariantTransform<TInput, TOutput>, ITransform, 
	IUnsupervisedLearning<DiscretizationTInput, TOutputOptions, TInput, TOutput>

<SerializableAttribute>
Public Class Options
	Inherits ColumnOptionsBase(Of Discretization(Of TInput, TOutput))
	Implements ITransform(Of TInput, TOutput), ICovariantTransform(Of TInput, TOutput), 
	ITransform, IUnsupervisedLearning(Of DiscretizationTInput, TOutputOptions, TInput, TOutput)

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The DiscretizationTInput, TOutputOptions generic type exposes the following members.

Constructors

	Name	Description
	DiscretizationTInput, TOutputOptions	Constructs a new Options object.
	DiscretizationTInput, TOutputOptions(String)	Constructs a new Options object for the given column.
	DiscretizationTInput, TOutputOptions(String, DictionaryExpressionFuncTInput, Boolean, ExpressionFuncTInput, TOutput)	Constructs a new Options object for the given column.

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Properties

	Name	Description
	ColumnName	Gets or sets the name of the column that the options will apply to. (Inherited from ColumnOptionsBaseTFilter.)
	Mapping	Gets the map between matching rules and the output that should be produced/inserted when they match.
	NumberOfInputs	Gets the number of inputs accepted by the model (value will be 1).
	NumberOfOutputs	Gets the number of outputs generated by the model (value will be 1).
	NumberOfSymbols	Gets the number of symbols used to code this variable.
	Owner	Gets or sets the filter to which these options belong to. (Inherited from ColumnOptionsBaseTFilter.)
	Tag	Gets or sets a user-determined object associated with this column. (Inherited from ColumnOptionsBaseTFilter.)
	Token	Gets or sets a cancellation token that can be used to stop the learning algorithm while it is running. (Inherited from ColumnOptionsBaseTFilter.)

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Methods

	Name	Description
	Decide(TInput)	Computes a class-label decision for a given input.
	Decide(TInput)	Computes class-label decisions for each vector in the given input.
	Decide(TInput, TOutput)	Computes class-label decisions for each vector in the given input.
	Equals	Determines whether the specified object is equal to the current object. (Inherited from Object.)
	Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	Learn(DataRow, Double)	Learns a model that can map the given inputs to the desired outputs.
	Learn(DataTable, Double)	Learns a model that can map the given inputs to the desired outputs.
	Learn(Object, Double)	Learns a model that can map the given inputs to the desired outputs.
	Learn(TInput, Double)	Learns a model that can map the given inputs to the desired outputs.
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	ToString	Returns a String that represents this instance. (Inherited from ColumnOptionsBaseTFilter.)
	Transform(DataRow)	Applies the transformation to an input, producing an associated output.
	Transform(DataRow)	Applies the transformation to an input, producing an associated output.
	Transform(TInput)	Applies the transformation to an input, producing an associated output.
	Transform(TInput)	Applies the transformation to a set of input vectors, producing an associated set of output vectors.
	Transform(DataRow, TOutput)	Applies the transformation to a set of input vectors, producing an associated set of output vectors.
	Transform(TInput, TOutput)	Applies the transformation to a set of input vectors, producing an associated set of output vectors.

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Extension Methods

	Name	Description
	HasMethod	Checks whether an object implements a method with the given name. (Defined by ExtensionMethods.)
	IsEqual	Compares 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.)

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Reference

Accord.Statistics.Filters Namespace

DiscretizationAddLanguageSpecificTextSet("LSTCC44FE7C_0?cs=&lt;|vb=(Of |cpp=&lt;|fs=&lt;'|nu=(");TInput, TOutputAddLanguageSpecificTextSet("LSTCC44FE7C_1?cs=&gt;|vb=)|cpp=&gt;|fs=&gt;|nu=)");AddLanguageSpecificTextSet("LSTCC44FE7C_2?cpp=::|nu=.");Options Class

Reference

DiscretizationTInput, TOutputOptions Class