woe_table: Crosstable with woe between a binary outcome and a predictor...

In embed: Extra Recipes for Encoding Predictors

Crosstable with woe between a binary outcome and a predictor variable.

Description

Calculates some summaries and the WoE (Weight of Evidence) between a binary outcome and a given predictor variable. Used to biuld the dictionary.

Usage

woe_table(predictor, outcome, Laplace = 1e-06, call = rlang::caller_env(0))

Arguments

predictor	A atomic vector, usualy with few distinct values.
outcome	The dependent variable. A atomic vector with exactly 2 distinct values.
Laplace	The pseudocount parameter of the Laplace Smoothing estimator. Default to 1e-6. Value to avoid -Inf/Inf from predictor category with only one outcome class. Set to 0 to allow Inf/-Inf.
call	The execution environment of a currently running function, e.g. caller_env(). The function will be mentioned in error messages as the source of the error. See the call argument of rlang::abort() for more information.

Value

a tibble with counts, proportions and woe. Warning: woe can possibly be -Inf. Use 'Laplace' arg to avoid that.

References

Kullback, S. (1959). Information Theory and Statistics. Wiley, New York.

Hastie, T., Tibshirani, R. and Friedman, J. (1986). Elements of Statistical Learning, Second Edition, Springer, 2009.

Good, I. J. (1985), "Weight of evidence: A brief survey", Bayesian Statistics, 2, pp.249-270.

embed documentation built on May 29, 2024, 9:59 a.m.