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LinearNormalizer

Normalizes the input matrix column-wise. The normalization can be executed so that

The common mean level of a column can be configured with a parameter. Normalization is done by subtracting the actual mean of each column and adding the common mean level.

If a column contains missing values, the mean is computed from non-missing values.

Version 1.0
Bundle tools
Categories Normalization
Specialties generic
Authors Kari Nousiainen (Kari.Nousiainen@Helsinki.FI), Ville Rantanen (ville.rantanen@helsinki.fi)
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Requires R
Source files component.xml LinearNormalizer.r
Usage Example with default values

Type parameters (generics)

Inputs

Name Type Mandatory Description
in T (generic) Mandatory Input matrix.

Outputs

Name Type Description
out T (generic) Output matrix where each column has the same mean.

Parameters

Name Type Default Description
excludeColumns string "" List of columns excluded from normalization. Normalizes all the numeric columns, so use this if your ID is numeric.
group string "" Label of the column that provides grouping. If given, the normalization is done individually for each unique group instead of the whole table.
lengthOfRange float 2 Length of the range. This parameter is used only with range normalization.
meanOfRange float 0 Common mean level. Each column will have a mean defined by this parameter when using method "mean". When using method "median" this value is added to every value after substraction by median. When using method "range" this parameters shows the mean of the range. This parameter is added to every value after normalization when using "z", "zMedian", or "unit variance" methods.
method string "mean" Possible values are "mean", "median", "range", "z", "zMedian" and "unitVariance" normalizations.

Test cases

Test case Parameters IN
in
OUT
out
case1 (missing) in out
case2_median properties in out

method=median,
meanOfRange=10,
excludeColumns=Status,Expected

case3_grouping properties in out

method=mean,
meanOfRange=0,
group=Group


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