Extreme Optimization™: Complexity made simple.

Math and Statistics
Libraries for .NET

  • Home
  • Features
    • Math Library
    • Vector and Matrix Library
    • Statistics Library
    • Performance
    • Usability
  • Documentation
    • Introduction
    • Math Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Reference
  • Resources
    • Downloads
    • QuickStart Samples
    • Sample Applications
    • Frequently Asked Questions
    • Technical Support
  • Blog
  • Order
  • Company
    • About us
    • Testimonials
    • Customers
    • Press Releases
    • Careers
    • Partners
    • Contact us
Introduction
Deployment Guide
Nuget packages
Configuration
Using Parallelism
Expand Mathematics Library User's GuideMathematics Library User's Guide
Expand Vector and Matrix Library User's GuideVector and Matrix Library User's Guide
Expand Data Analysis Library User's GuideData Analysis Library User's Guide
Expand Statistics Library User's GuideStatistics Library User's Guide
Expand Data Access Library User's GuideData Access Library User's Guide
Expand ReferenceReference
  • Extreme Optimization
    • Features
    • Solutions
    • Documentation
    • QuickStart Samples
    • Sample Applications
    • Downloads
    • Technical Support
    • Download trial
    • How to buy
    • Blog
    • Company
    • Resources
  • Documentation
    • Introduction
    • Deployment Guide
    • Nuget packages
    • Configuration
    • Using Parallelism
    • Mathematics Library User's Guide
    • Vector and Matrix Library User's Guide
    • Data Analysis Library User's Guide
    • Statistics Library User's Guide
    • Data Access Library User's Guide
    • Reference
  • Reference
    • Extreme
    • Extreme.Collections
    • Extreme.Data
    • Extreme.Data.Json
    • Extreme.Data.Matlab
    • Extreme.Data.R
    • Extreme.Data.Stata
    • Extreme.Data.Text
    • Extreme.DataAnalysis
    • Extreme.DataAnalysis.Linq
    • Extreme.DataAnalysis.Models
    • Extreme.Mathematics
    • Extreme.Mathematics.Algorithms
    • Extreme.Mathematics.Calculus
    • Extreme.Mathematics.Calculus.OrdinaryDifferentialEquations
    • Extreme.Mathematics.Curves
    • Extreme.Mathematics.Curves.Nonlinear
    • Extreme.Mathematics.Distributed
    • Extreme.Mathematics.EquationSolvers
    • Extreme.Mathematics.Generic
    • Extreme.Mathematics.LinearAlgebra
    • Extreme.Mathematics.LinearAlgebra.Implementation
    • Extreme.Mathematics.LinearAlgebra.IterativeSolvers
    • Extreme.Mathematics.LinearAlgebra.IterativeSolvers.Preconditioners
    • Extreme.Mathematics.Optimization
    • Extreme.Mathematics.Optimization.LineSearches
    • Extreme.Mathematics.Random
    • Extreme.Mathematics.SignalProcessing
    • Extreme.Providers
    • Extreme.Providers.InteropServices
    • Extreme.Statistics
    • Extreme.Statistics.Distributions
    • Extreme.Statistics.Multivariate
    • Extreme.Statistics.Tests
    • Extreme.Statistics.TimeSeriesAnalysis
  • Extreme.DataAnalysis.Models
    • ClassificationModel(T) Class
    • ClusteringModel(T) Class
    • ITransformationModel Interface
    • Model Class
    • ModelExtensions Class
    • ModelFitOptions Class
    • ModelInput Class
    • ModelInputCategory Enumeration
    • ModelInputFormat Enumeration
    • ModelInputGroup Class
    • ModelSerialization Enumeration
    • ModelStatus Enumeration
    • ModelTerm Class
    • ModelTermCollection Class
    • ModelTermKind Enumeration
    • RegressionModel(T) Class
    • TransformationModel(T) Class
  • ModelInputGroup Class
    • Properties
    • Methods
  • Methods
    • AddIntercept Method
    • AsCategorical Method
    • AsCategoricalColumns Method
    • AsMatrix(T) Method
    • AsRowVectors(T) Method
    • AsVector(T) Method
    • GetEncoding Method
    • InferSchema Method Overloads
    • Populate Method Overloads
    • RemoveConstantColumns Method
    • RemoveIntercept Method
    • SetEncoding Method
  • AsCategorical Method

ModelInputGroupAsCategorical Method

Extreme Optimization Numerical Libraries for .NET Professional
Returns a representation of the data as an untyped categorical vector in accordance with a specification.

Namespace:  Extreme.DataAnalysis.Models
Assembly:  Extreme.Numerics (in Extreme.Numerics.dll) Version: 8.1.1
Syntax

C#
VB
C++
F#
Copy
public ICategoricalVector AsCategorical()
Public Function AsCategorical As ICategoricalVector
public:
ICategoricalVector^ AsCategorical()
member AsCategorical : unit -> ICategoricalVector 

Return Value

Type: ICategoricalVector
A categorical vector containing the data in Data.
Exceptions

ExceptionCondition
DimensionMismatchException

The result contains more than one column.

See Also

Reference

ModelInputGroup Class
Extreme.DataAnalysis.Models Namespace

Copyright (c) 2004-2021 ExoAnalytics Inc.

Send comments on this topic to support@extremeoptimization.com

Copyright © 2004-2021, Extreme Optimization. All rights reserved.
Extreme Optimization, Complexity made simple, M#, and M Sharp are trademarks of ExoAnalytics Inc.
Microsoft, Visual C#, Visual Basic, Visual Studio, Visual Studio.NET, and the Optimized for Visual Studio logo
are registered trademarks of Microsoft Corporation.