iv.mult: Calculate Information Value for defined columns in data frame

In tomasgreif/woe: Tools to calculate Weight of Evidence (WoE) and Information Value.

Description

Calculates information value for defined columns in given data frame. Columns can have numeric or character type (including factors).

Usage

  iv.mult(df, y, summary = FALSE, vars = NULL,
    verbose = FALSE, rcontrol = NULL)

Arguments

df	data frame with at least two columns
y	column (integer or factor) with binary outcome. It is suggested that y is factor with two levels "bad" and "good" If there are no levels good/bad than the following assumptions are applied - if y is integer, than 0=good and 1=bad. If y is factor than level 2 is assumed to mean bad and 1 good.
summary	Only total information value for variable is returned when summary is TRUE. Output is sorted by information value, starting with highest value.
vars	List of variables. If not specified, all character variables will be used
verbose	Prints additional details when TRUE. Useful mainly for debugging.
rcontrol	Additional parameters used for rpart tree generation. Use ?rpart.control() to get more details.

Details

Information Value (IV) is concept used in risk management to assess predictive power of variable. IV is defined as: WoE (Weight of Evidence) is defined as:

Examples

iv.mult(german_data,"gb")
iv.mult(german_data,"gb",TRUE)
iv.mult(german_data,"gb",TRUE,c("ca_status","housing","job","duration")) # str(german_data)
iv.mult(german_data,"gb",vars=c("ca_status","housing","job","duration"))
iv.mult(german_data,"gb",summary=TRUE, verbose=TRUE)
# Use varlist() function to get all numeric variables
iv.mult(german_data,y="gb",vars=varlist(german_data,"numeric"))

tomasgreif/woe documentation built on May 31, 2019, 5:16 p.m.