ScaleNormalize: Re-scales input matrix proportinally to item popularity

In rsparse: Statistical Learning on Sparse Matrices

Re-scales input matrix proportinally to item popularity

Description

scales input user-item interaction matrix as per eq (16) from the paper. Usage of such rescaled matrix with [PureSVD] model will be equal to running PureSVD on the scaled cosine-based inter-item similarity matrix.

Public fields

norm

which norm model should make equal to one

scale

how to rescale norm vector

Methods

Public methods

• ScaleNormalize$new()

• ScaleNormalize$fit()

• ScaleNormalize$transform()

• ScaleNormalize$fit_transform()

• ScaleNormalize$clone()

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Method new()

creates model

Usage

ScaleNormalize$new(scale = 0.5, norm = 2, target = c("rows", "columns"))

Arguments

scale

numeric, how to rescale norm vector

norm

numeric, which norm model should make equal to one

target

character, defines whether rows or columns should be rescaled

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Method fit()

fits the modes

Usage

ScaleNormalize$fit(x)

Arguments

x

input sparse matrix

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Method transform()

transforms new matrix

Usage

ScaleNormalize$transform(x)

Arguments

x

input sparse matrix

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Method fit_transform()

fits the model and transforms input

Usage

ScaleNormalize$fit_transform(x)

Arguments

x

input sparse matrix

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Method clone()

The objects of this class are cloneable with this method.

Usage

ScaleNormalize$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

See EigenRec: Generalizing PureSVD for Effective and Efficient Top-N Recommendations for details.

rsparse documentation built on June 28, 2024, 5:06 p.m.