AutoCatalog.Featurizer Method

Definition

Namespace:

Microsoft.ML.AutoML

Assembly:

Microsoft.ML.AutoML.dll

Package:

Microsoft.ML.AutoML v0.21.1

Overloads

Featurizer(IDataView, ColumnInformation, String)

Create a single featurize pipeline according to columnInformation. This function will collect all columns in columnInformation, featurizing them using Microsoft.ML.AutoML.AutoCatalog.CatalogFeaturizer(System.String[],System.String[]), Microsoft.ML.AutoML.AutoCatalog.NumericFeaturizer(System.String[],System.String[]) or Microsoft.ML.AutoML.AutoCatalog.TextFeaturizer(System.String,System.String). And combine them into a single feature column as output.

Featurizer(IDataView, String, String[], String[], String[], String[], String[])

Create a single featurize pipeline according to data. This function will collect all columns in data and not in excludeColumns, featurizing them using Microsoft.ML.AutoML.AutoCatalog.CatalogFeaturizer(System.String[],System.String[]), Microsoft.ML.AutoML.AutoCatalog.NumericFeaturizer(System.String[],System.String[]) or Microsoft.ML.AutoML.AutoCatalog.TextFeaturizer(System.String,System.String). And combine them into a single feature column as output.

Featurizer(IDataView, ColumnInformation, String)

Create a single featurize pipeline according to columnInformation. This function will collect all columns in columnInformation, featurizing them using Microsoft.ML.AutoML.AutoCatalog.CatalogFeaturizer(System.String[],System.String[]), Microsoft.ML.AutoML.AutoCatalog.NumericFeaturizer(System.String[],System.String[]) or Microsoft.ML.AutoML.AutoCatalog.TextFeaturizer(System.String,System.String). And combine them into a single feature column as output.

public Microsoft.ML.AutoML.SweepablePipeline Featurizer (Microsoft.ML.IDataView data, Microsoft.ML.AutoML.ColumnInformation columnInformation, string outputColumnName = "Features");

member this.Featurizer : Microsoft.ML.IDataView * Microsoft.ML.AutoML.ColumnInformation * string -> Microsoft.ML.AutoML.SweepablePipeline

Public Function Featurizer (data As IDataView, columnInformation As ColumnInformation, Optional outputColumnName As String = "Features") As SweepablePipeline

Parameters

data

IDataView

input data.

columnInformation

ColumnInformation

column information.

outputColumnName

String

output feature column.

Returns

SweepablePipeline

A SweepablePipeline for featurization.

Featurizer(IDataView, String, String[], String[], String[], String[], String[])

Create a single featurize pipeline according to data. This function will collect all columns in data and not in excludeColumns, featurizing them using Microsoft.ML.AutoML.AutoCatalog.CatalogFeaturizer(System.String[],System.String[]), Microsoft.ML.AutoML.AutoCatalog.NumericFeaturizer(System.String[],System.String[]) or Microsoft.ML.AutoML.AutoCatalog.TextFeaturizer(System.String,System.String). And combine them into a single feature column as output.

public Microsoft.ML.AutoML.SweepablePipeline Featurizer (Microsoft.ML.IDataView data, string outputColumnName = "Features", string[] catelogicalColumns = default, string[] numericColumns = default, string[] textColumns = default, string[] imagePathColumns = default, string[] excludeColumns = default);

member this.Featurizer : Microsoft.ML.IDataView * string * string[] * string[] * string[] * string[] * string[] -> Microsoft.ML.AutoML.SweepablePipeline

Public Function Featurizer (data As IDataView, Optional outputColumnName As String = "Features", Optional catelogicalColumns As String() = Nothing, Optional numericColumns As String() = Nothing, Optional textColumns As String() = Nothing, Optional imagePathColumns As String() = Nothing, Optional excludeColumns As String() = Nothing) As SweepablePipeline

Parameters

data

IDataView

input data.

outputColumnName

String

output feature column.

catelogicalColumns

String[]

columns that should be treated as catalog. If not specified, it will automatically infer if a column is catalog or not.

numericColumns

String[]

columns that should be treated as numeric. If not specified, it will automatically infer if a column is catalog or not.

textColumns

String[]

columns that should be treated as text. If not specified, it will automatically infer if a column is catalog or not.

imagePathColumns

String[]

columns that should be treated as image path. If not specified, it will automatically infer if a column is catalog or not.

excludeColumns

String[]

columns that won't be included when featurizing, like label

Returns

SweepablePipeline