get_iv_all: Calculate Information Value (IV) 'get_iv' is used to...

In creditmodel: Toolkit for Credit Modeling, Analysis and Visualization

Description

Calculate Information Value (IV) get_iv is used to calculate Information Value (IV) of an independent variable. get_iv_all can loop through IV for all specified independent variables.

Usage

get_iv_all(
  dat,
  x_list = NULL,
  ex_cols = NULL,
  breaks_list = NULL,
  target = NULL,
  pos_flag = NULL,
  best = TRUE,
  equal_bins = FALSE,
  tree_control = NULL,
  bins_control = NULL,
  g = 10,
  parallel = FALSE,
  note = FALSE
)

get_iv(
  dat,
  x,
  target = NULL,
  pos_flag = NULL,
  breaks = NULL,
  breaks_list = NULL,
  best = TRUE,
  equal_bins = FALSE,
  tree_control = NULL,
  bins_control = NULL,
  g = 10,
  note = FALSE
)

Arguments

dat	A data.frame with independent variables and target variable.
x_list	Names of independent variables.
ex_cols	A list of excluded variables. Regular expressions can also be used to match variable names. Default is NULL.
breaks_list	A table containing a list of splitting points for each independent variable. Default is NULL.
target	The name of target variable.
pos_flag	Value of positive class, Default is "1".
best	Logical, merge initial breaks to get optimal breaks for binning.
equal_bins	Logical, generates initial breaks for equal frequency binning.
tree_control	Parameters of using Decision Tree to segment initial breaks. See detials: get_tree_breaks
bins_control	Parameters used to control binning. See detials: select_best_class, select_best_breaks
g	Number of initial breakpoints for equal frequency binning.
parallel	Logical, parallel computing. Default is FALSE.
note	Logical, outputs info. Default is TRUE.
x	The name of an independent variable.
breaks	Splitting points for an independent variable. Default is NULL.

Details

IV Rules of Thumb for evaluating the strength a predictor Less than 0.02:unpredictive 0.02 to 0.1:weak 0.1 to 0.3:medium 0.3 + :strong

References

Information Value Statistic:Bruce Lund, Magnify Analytics Solutions, a Division of Marketing Associates, Detroit, MI(Paper AA - 14 - 2013)

See Also

get_iv,get_iv_all,get_psi,get_psi_all

Examples

get_iv_all(dat = UCICreditCard,
 x_list = names(UCICreditCard)[3:10],
 equal_bins = TRUE, best = FALSE,
 target = "default.payment.next.month",
 ex_cols = "ID|apply_date")
get_iv(UCICreditCard, x = "PAY_3",
       equal_bins = TRUE, best = FALSE,
 target = "default.payment.next.month")

Example output

Package 'creditmodel' version 1.2.7
    Feature    IV     strength
1 LIMIT_BAL 0.178       Strong
2       SEX 0.009 Unpredictive
3 EDUCATION 0.038         Weak
4  MARRIAGE 0.008 Unpredictive
5       AGE 0.021         Weak
6     PAY_0 0.874  Very Strong
7     PAY_2 0.545  Very Strong
8     PAY_3 0.413  Very Strong
  Feature    IV    strength
1   PAY_3 0.413 Very Strong

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