set_validation_data: Add 'validation_data' to a rulelist

In tidyrules: Utilities to Retrieve Rulelists from Model Fits, Filter, Prune, Reorder and Predict on Unseen Data

Add validation_data to a rulelist

Description

Returns a rulelist with three new attributes set: validation_data, y_name and weight. Methods such as augment, calculate, prune, reorder require this to be set.

Usage

set_validation_data(x, validation_data, y_name, weight = 1)

Arguments

x	A rulelist
validation_data	(dataframe) Data to used for computing some metrics. It is expected to contain y_name column.
y_name	(string) Name of the dependent variable column.
weight	(non-negative numeric vector, default: 1) Weight per observation/row of validation_data. This is expected to have same length as the number of rows in validation_data. Only exception is when it is a single positive number, which means that all rows have equal weight.

Value

A rulelist with some extra attributes set.

See Also

rulelist, tidy, augment, predict, calculate, prune, reorder

Other Core Rulelist Utility: set_keys()

Examples

att = modeldata::attrition
set.seed(100)
index = sample(c(TRUE, FALSE), nrow(att), replace = TRUE)
model_c5 = C50::C5.0(Attrition ~., data = att[index, ], rules = TRUE)

tidy_c5 = tidy(model_c5)
tidy_c5

tidy_c5_2 = set_validation_data(tidy_c5,
                                validation_data = att[!index, ],
                                y_name = "Attrition",
                                weight = 1 # default
                                )
tidy_c5_2
tidy_c5 # not altered

tidyrules documentation built on June 30, 2024, 1:07 a.m.