filterdb

Methods for Supervised Filtering of Predictors

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output: github_document

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

filterdb

The goal of filterdb is to ...

Installation

You can install the development version of filterdb like so:

require(pak)
pak::pak("topepo/filterdb")

Example

#| results: hide
#| message: false
#| warning: false
library(filterdb)
library(dplyr)
library(modeldata)

data(ames)
ames$Sale_Price <- log10(ames$Sale_Price)
ames_scores <-
  importance_metrics(
    ames %>% select(-Sale_Price),
    y = ames %>% select(Sale_Price),
    methods = c("corr_rank", "imp_rf", "max_diff")
  )
ames_scores
results <- tidy(ames_scores)
results
head(results$corr_rank)
results %>% 
  filter(corr_rank < 1/3 & max_diff >= 0.4) %>% 
  slice_max(imp_rf, n = 5)

Code of Conduct

Please note that the filterdb project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.