reduce_high_cor_filter {creditmodel}R Documentation

Filtering highly correlated variables with reduce method

Description

reduce_high_cor_filter is function for filtering highly correlated variables with reduce method.

Usage

reduce_high_cor_filter(
  dat,
  x_list = NULL,
  size = ncol(dat)/10,
  p = 0.95,
  com_list = NULL,
  ex_cols = NULL,
  cor_class = TRUE,
  parallel = FALSE
)

Arguments

dat

A data.frame with independent variables.

x_list

Names of independent variables.

size

Size of vairable group.

p

Threshold of correlation between features. Default is 0.7.

com_list

A data.frame with important values of each variable. eg : IV_list

ex_cols

A list of excluded variables. Regular expressions can also be used to match variable names. Default is NULL.

cor_class

Culculate catagery variables's correlation matrix. Default is FALSE.

parallel

Logical, parallel computing. Default is FALSE.


[Package creditmodel version 1.3.0 Index]