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CAISEr package

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CAISEr: Comparing Algorithms with Iterative Sample-size Estimation in R

Author/maintainer:

Contributors:

[1] Department of Computer Science, Aston University, Birmingham UK
[2] Operations Research and Complex Systems Laboratory, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
[3] Department of Computer Science, CEFET-MG, Brazil


Implementation of R package CAISEr, with routines for automatically determining the sample size needed for performing comparative experiments with multiple algorithms on multiple problem instances.

To install the most up-to-date version directly from Github, simply type:

library(devtools)
devtools::install_github("fcampelo/CAISEr")

The most recent CRAN release of the package is also available for installation directly from the R prompt, using:

install.packages("CAISEr")

For instructions and examples of use, please take a look at the vignette Adapting Algorithms for CAISEr, and at the package documentation, particularly functions run_experiment(), run_nreps() and calc_instances().


Please send any bug reports, questions or suggestions directly to the package authors listed at the top of this document: https://github.com/fcampelo/CAISEr/issues

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caiser's Issues

Reuse algorithmic runs

The package currently can restart interrupted experiments, but assumes that files in the target directory were generated by exactly the same experimental configuration.

It would be interesting to add the ability to check results files, extract exactly the observations of each algorithm on each run, and pre-fill the raw results table Xk (created within calc_nreps()), so that the package would only run new observations if strictly needed.

The internal data structures / functions may need to be slightly modified.

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