low_variance_filter: Filtering Low Variance Variables

In creditmodel: Toolkit for Credit Modeling, Analysis and Visualization

Description

low_variance_filter is for removing variables with repeated values up to a certain percentage.

Usage

low_variance_filter(
  dat,
  lvp = 0.97,
  only_NA = FALSE,
  note = FALSE,
  ex_cols = NULL
)

Arguments

dat	A data frame with x and target.
lvp	The maximum percent of unique values (including NAs).
only_NA	Logical, only process variables which NA's rate are more than lvp.
note	Logical.Outputs info.Default is TRUE.
ex_cols	A list of excluded variables. Default is NULL.

Value

A data.frame

Examples

dat = low_variance_filter(lendingclub[1:1000, ], lvp = 0.9)

creditmodel documentation built on Jan. 7, 2022, 5:06 p.m.