Purge training data from a model

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Description

Most R model implementations store the training data within the fitted object, often many times. It can be useful to remove the embedded data for portability, especially if the only required functionality is to predict on new data.

Usage

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purge(model)

## Default S3 method:
purge(model)

## S3 method for class 'glm'
purge(model)

## S3 method for class 'lm'
purge(model)

## S3 method for class 'merMod'
purge(model)

## S3 method for class 'glmerMod'
purge(model)

## S3 method for class 'rpart'
purge(model)

## S3 method for class 'randomForest'
purge(model)

## S3 method for class 'ranger'
purge(model)

## S3 method for class 'coxph'
purge(model)

Arguments

model

A fitted R model object

Value

A fitted R model object, purged of its training data, but retaining its predict functionality on new data

Methods (by class)

  • default: Default purge returns a copy of the model

  • glm: Purges a glm model

  • lm: Purges an lm model

  • merMod: Purges a merMod, linear mixed-effects model

  • glmerMod: Purges a glmerMod, generalized linear mixed-effects model

  • rpart: Purges an rpart model

  • randomForest: Purges a random forest model

  • ranger: Purges a ranger model for classification, regression, or survival

  • coxph: Purges a coxph model

Examples

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x <- rnorm(1000)
y <- x + rnorm(1000)
unpurged.model <- lm(y ~ x)
purged.model <- purge(unpurged.model)
object.size(unpurged.model)
object.size(purged.model)

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