KPI_summary_table: KPI summary table

In ASML: Algorithm Portfolio Selection with Machine Learning

KPI summary table

Description

Generates a summary table with the values of the KPI.

Function that generates a summary table of the KPI values. Optimal is the value of the KPI when choosing the best option for each instance. It's the best that we could do with respect to that KPI. Best is the value of the KPI for the best option overall according to the KPI. ML is the value of the KPI choosing for each instance the option selected by the learning.

Usage

KPI_summary_table(data_object, ...)

## S3 method for class 'as_data'
KPI_summary_table(
  data_object,
  predictions = NULL,
  test = TRUE,
  normalized = FALSE,
  ...
)

Arguments

data_object	an object of class as_data.
...	other parameters.
predictions	a data frame with the predicted KPI for each algorithm (columns) and for each instance (rows). If NULL, the table won't include a ML column.
test	flag that indicates whether the function should use test data or training data.
normalized	whether to use the original values of the KPI or the normalized ones used for the learning.

Value

A table, result of the respective KPI_summary_table method.

A table with the statistics of the pace.

Examples

data(branchingsmall)
data_object <- partition_and_normalize(branchingsmall$x, branchingsmall$y, test_size = 0.3,
family_column = 1, split_by_family = TRUE)
training <- AStrain(data_object, method = "glm")
predictions <- ASpredict(training, newdata = data_object$x.test)
KPI_summary_table(data_object, predictions = predictions)

ASML documentation built on April 3, 2025, 8:47 p.m.