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Add-NormalizeGlobalContrastTransform.md

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Add-NormalizeGlobalContrastTransform

Scale each value in a row by subtracting the mean of the row data and divide by either the standard deviation or l2-norm (of the row data), and multiply by a configurable scale factor (default 2).

Description

Scale each value in a row by subtracting the mean of the row data and divide by either the standard deviation or l2-norm (of the row data), and multiply by a configurable scale factor (default 2).

Syntax

Add-NormalizeGlobalContrastTransform [-OutputColumn] <String> [[-InputColumn] <String>] [-Scale <Single>] [-DontEnsureZeroMean] [-EnsureUnitStandardDeviation] [-AppendTo <EstimatorChain<ITransformer>>] [-AppendScope <TransformerScope>] [-Context <MLContext>] [<CommonParameters>]

Parameters

-OutputColumn

Name of the column resulting from the transformation of inputColumnName. This column's data type will be the same as the input column's data type.

Type: System.String
Required: True
Position: 0
Default value: None
Accept pipeline input: False
Accept wildcard characters: False

-InputColumn

Name of the column to normalize. If set to null, the value of the outputColumnName will be used as source. This estimator operates over known-sized vectors of Single.

Type: System.String
Required: False
Position: 1
Default value: null
Accept pipeline input: False
Accept wildcard characters: False

-Scale

Scale features by this value.

Type: System.Single
Required: False
Position: named
Default value: 1
Accept pipeline input: False
Accept wildcard characters: False

-DontEnsureZeroMean

Subtract mean from each value before normalizing and use the raw input otherwise.

Type: System.Management.Automation.SwitchParameter
Required: False
Position: named
Default value: False
Accept pipeline input: False
Accept wildcard characters: False

-EnsureUnitStandardDeviation

If true, the resulting vector's standard deviation would be one. Otherwise, the resulting vector's L2-norm would be one.

Type: System.Management.Automation.SwitchParameter
Required: False
Position: named
Default value: False
Accept pipeline input: False
Accept wildcard characters: False

-AppendTo

Append the created estimator to the end of this chain.

Type: Microsoft.ML.Data.EstimatorChain<Microsoft.ML.ITransformer>
Required: False
Position: named
Default value: null
Accept pipeline input: True (ByValue)
Accept wildcard characters: False

-AppendScope

The scope allows for 'tagging' the estimators (and subsequently transformers) in the chain to be used 'only for training', 'for training and evaluation' etc.

Type: Microsoft.ML.Data.TransformerScope
Required: False
Position: named
Default value: Everything
Accept pipeline input: False
Accept wildcard characters: False

-Context

The context on which to perform the action. If omitted, the current (cached) context will be used.

Type: Microsoft.ML.MLContext
Required: False
Position: named
Default value: Current context
Accept pipeline input: False
Accept wildcard characters: False

Common parameters

This cmdlet supports the common parameters: Verbose, Debug, ErrorAction, ErrorVariable, WarningAction, WarningVariable, OutBuffer, PipelineVariable, and OutVariable. For more information, see about_CommonParameters.

Inputs

Type Description
Microsoft.ML.Data.EstimatorChain<Microsoft.ML.ITransformer> You can pipe the EstimatorChain to append to this cmdlet.

Outputs

Type Description
Microsoft.ML.Data.EstimatorChain<Microsoft.ML.ITransformer> This cmdlet returns the appended EstimatorChain.