Description Usage Arguments Details Value References Examples

Builds the woe dictionary of a set of predictor variables upon a given binary outcome. Convenient to make a woe version of the given set of predictor variables and also to allow one to tweak some woe values by hand.

1 | ```
dictionary(.data, outcome, ..., Laplace = 1e-06)
``` |

`.data` |
A tbl. The data.frame where the variables come from. |

`outcome` |
The bare name of the outcome variable with exactly 2 distinct values. |

`...` |
bare names of predictor variables or selectors accepted by |

`Laplace` |
Default to 1e-6. The |

You can pass a custom dictionary to `step_woe()`

. It must have the exactly
the same structure of the output of `dictionary()`

. One easy way to do this
is by tweaking an output returned from it.

a tibble with summaries and woe for every given predictor variable stacked up.

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.

1 | ```
mtcars %>% dictionary("am", cyl, gear:carb)
``` |

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