get_binary_corr_mat: Identify correlated features as a binary matrix

In SchlossLab/mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines

Identify correlated features as a binary matrix

Description

Identify correlated features as a binary matrix

Usage

get_binary_corr_mat(
  features,
  corr_thresh = 1,
  group_neg_corr = TRUE,
  corr_method = "spearman"
)

Arguments

features	a dataframe with each column as a feature for ML
corr_thresh	For feature importance, group correlations above or equal to corr_thresh (range 0 to 1; default: 1).
group_neg_corr	Whether to group negatively correlated features together (e.g. c(0,1) and c(1,0)).
corr_method	correlation method. options or the same as those supported by stats::cor: spearman, pearson, kendall. (default: spearman)

Value

A binary matrix of correlated features

Author(s)

Kelly Sovacool, [e-mail]

Examples

## Not run: 
features <- data.frame(
  a = 1:3, b = 2:4, c = c(1, 0, 1),
  d = (5:7), e = c(5, 1, 4)
)
get_binary_corr_mat(features)

## End(Not run)

SchlossLab/mikropml documentation built on Aug. 24, 2023, 9:51 p.m.