Transformations/Pipelines

# Transformations/Pipelines API Reference

## Functions

``BoxCox(lambda)``

Returns a BoxCox transform operator/function. To be used in a pipeline.

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``(T::Center)(Z; inverse = false)``

Centers data in array `Z` column-wise according to learned mean centers in Center object `T`.

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``Center(Z)``

Acquires the mean of each column in `Z` provided and returns a transform that will subtract those column means from any future data.

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``(T::CenterScale)(Z; inverse = false)``

Centers and Scales data in array `Z` column-wise according to learned measures of central tendancy in Scale object `T`.

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``CenterScale(Z)``

This is a composition of Center and Scale (in that order).

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``(T::QuantileTrim)(X, inverse = false)``

Trims data in array `X` columns wise according to learned quantiles in QuantileTrim object `T` This function does NOT have an inverse.

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``QuantileTrim(Z; quantiles::Tuple{Float64,Float64} = (0.05, 0.95) )``

Trims values above or below the specified columnwise quantiles to the quantile values themselves.

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``(T::RangeNorm)(Z; inverse = false)``

Scales and shifts data in array `Z` column-wise according to learned min-maxes in RangeNorm object `T`.

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``RangeNorm( Z )``

Acquires the minimum and maximum of each column in `Z` provided and returns a transform that performs the following operation (Z - min(X))/(max(X) - min(X)) on any future data. This has the important effect of scaling all values observed in the range of `Z` to be between 0 and 1 with respect to each column.

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``(T::Scale)(Z; inverse = false)``

Scales data in array `Z` column-wise according to learned standard deviations in Scale object `T`.

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``Scale(Z)``

Acquires the standard deviation of each column in `Z` provided and returns a transform that will divide those column-wise standard deviation from any future data.

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``Logit(Z; inverse = false)``

Logit transforms (`ln( X / (1 - X) ))`) every element in `Z`. The inverse may also be applied. Warning: This can return Infs and NaNs if elements of Z are not suited to the transform

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``Pipeline( X, FnStack... )``

Construct a pipeline object from vector/tuple of `Transforms`. The Transforms vector are effectively a vector of functions which transform data.

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``Pipeline(Transforms)``

Constructs a transformation pipeline from vector/tuple of `Transforms`. The Transforms vector are effectively a vector of functions which transform data.

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``PipelineInPlace( X, FnStack...)``

Construct a pipeline object from vector/tuple of `Transforms`. The Transforms vector are effectively a vector of functions which transform data. This function makes "inplace" changes to the Array `X` as though it has been sent through the pipeline. This is more efficient if memory is a concern, but can irreversibly transform data in memory depending on the transforms in the pipeline.

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``(P::pipeline)(X; inverse = false)``

Applies the stored transformations in a pipeline object `P` to data in X. The inverse flag can allow for the transformations to be reversed provided they are invertible functions.

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