ASML - Algorithm Portfolio Selection with Machine Learning
A wrapper for machine learning (ML) methods to select
among a portfolio of algorithms based on the value of a key
performance indicator (KPI). A number of features is used to
adjust a model to predict the value of the KPI for each
algorithm, then, for a new value of the features the KPI is
estimated and the algorithm with the best one is chosen. To
learn it can use the regression methods in 'caret' package or a
custom function defined by the user. Several graphics available
to analyze the results obtained. This library has been used in
Ghaddar et al. (2023) <doi:10.1287/ijoc.2022.0090>).