case-weight-helpers: Helpers for steps with case weights

In recipes: Preprocessing and Feature Engineering Steps for Modeling

Helpers for steps with case weights

Description

These functions can be used to do basic calculations with or without case weights.

Usage

get_case_weights(info, .data)

averages(x, wts = NULL, na_rm = TRUE)

medians(x, wts = NULL)

variances(x, wts = NULL, na_rm = TRUE)

correlations(x, wts = NULL, use = "everything", method = "pearson")

covariances(x, wts = NULL, use = "everything", method = "pearson")

pca_wts(x, wts = NULL)

are_weights_used(wts, unsupervised = FALSE)

Arguments

info	A data frame from the info argument within steps
.data	The training data
x	A numeric vector or a data frame
wts	A vector of case weights
na_rm	A logical value indicating whether NA values should be removed during computations.
use	Used by correlations() or covariances() to pass argument to cor() or cov()
method	Used by correlations() or covariances() to pass argument to cor() or cov()
unsupervised	Can the step handle unsupervised weights

Details

get_case_weights() is designed for developers of recipe steps, to return a column with the role of "case weight" as a vector.

For the other functions, rows with missing case weights are removed from calculations.

For averages() and variances(), missing values in the data (not the case weights) only affect the calculations for those rows. For correlations(), the correlation matrix computation first removes rows with any missing values (equal to the "complete.obs" strategy in stats::cor()).

are_weights_used() is designed for developers of recipe steps and is used inside print method to determine how printing should be done.

recipes documentation built on Jan. 11, 2023, 5:14 p.m.