psi_iv_filter: Variable reduction based on Information Value & Population...
In creditmodel: Toolkit for Credit Modeling, Analysis and Visualization

Description Usage Arguments Value See Also Examples

psi_iv_filter is for selecting important and stable features using IV & PSI.

psi_iv_filter(
  dat,
  dat_test = NULL,
  target,
  x_list = NULL,
  breaks_list = NULL,
  pos_flag = NULL,
  ex_cols = NULL,
  occur_time = NULL,
  best = FALSE,
  equal_bins = TRUE,
  g = 10,
  sp_values = NULL,
  tree_control = list(p = 0.05, cp = 1e-06, xval = 5, maxdepth = 10),
  bins_control = list(bins_num = 10, bins_pct = 0.05, b_chi = 0.05, b_odds = 0.1, b_psi
    = 0.05, b_or = 0.15, mono = 0.3, odds_psi = 0.2, kc = 1),
  oot_pct = 0.7,
  psi_i = 0.1,
  iv_i = 0.01,
  cos_i = 0.7,
  vars_name = FALSE,
  note = TRUE,
  parallel = FALSE,
  save_data = FALSE,
  file_name = NULL,
  dir_path = tempdir(),
  ...
)

`dat`	A data.frame with independent variables and target variable.
`dat_test`	A data.frame of test data. Default is NULL.
`target`	The name of target variable.
`x_list`	Names of independent variables.
`breaks_list`	A table containing a list of splitting points for each independent variable. Default is NULL.
`pos_flag`	The value of positive class of target variable, default: "1".
`ex_cols`	A list of excluded variables. Regular expressions can also be used to match variable names. Default is NULL.
`occur_time`	The name of the variable that represents the time at which each observation takes place.
`best`	Logical, if TRUE, merge initial breaks to get optimal breaks for binning.
`equal_bins`	Logical, if TRUE, equal sample size initial breaks generates.If FALSE , tree breaks generates using desison tree.
`g`	Integer, number of initial bins for equal_bins.
`sp_values`	A list of missing values.
`tree_control`	the list of tree parameters.
`bins_control`	the list of parameters.
`oot_pct`	Percentage of observations retained for overtime test (especially to calculate PSI). Defualt is 0.7
`psi_i`	The maximum threshold of PSI. 0 <= psi_i <=1; 0.05 to 0.2 usually work. Default: 0.1
`iv_i`	The minimum threshold of IV. 0 < iv_i ; 0.01 to 0.1 usually work. Default: 0.01
`cos_i`	cos_similarity of posive rate of train and test. 0.7 to 0.9 usually work.Default: 0.5.
`vars_name`	Logical, output a list of filtered variables or table with detailed IV and PSI value of each variable. Default is FALSE.
`note`	Logical, outputs info. Default is TRUE.
`parallel`	Logical, parallel computing. Default is FALSE.
`save_data`	Logical, save results in locally specified folder. Default is FALSE.
`file_name`	The name for periodically saved results files. Default is "Feature_importance_IV_PSI".
`dir_path`	The path for periodically saved results files. Default is tempdir().
`...`	Other parameters.

A list with the following elements:

Feature Selected variables.
IV IV of variables.
PSI PSI of variables.
COS cos_similarity of posive rate of train and test.

xgb_filter, gbm_filter, feature_selector

psi_iv_filter(dat= UCICreditCard[1:1000,c(2,4,8:9,26)],
             target = "default.payment.next.month",
             occur_time = "apply_date",
             parallel = FALSE)