GRIDSEARCH: Stata module to optimize tuning parameter levels with a grid search

Matthias Schonlau ()
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Matthias Schonlau: University of Waterloo

Statistical Software Components from Boston College Department of Economics

Abstract: gridsearch runs a user-specified statistical learning (aka machine learning) algorithm repeatedly with a grid of values corresponding to one or two tuning parameters. This facilities the tuning of statistical learning algorithms. Examples of statistical learning algorithms that require tuning include support vector machines, gradient boosting, k-nearest neighbors, random forests. After evaluating all combinations of values according to criterion, gridsearch lists the best combination and the corresponding value of the criterion.

Language: Stata
Requires: Stata version 14 and crossvalidate from SSC (q.v.)
Keywords: machine learning; grid search; support vector machines; random forests (search for similar items in EconPapers)
Date: 2020-10-29, Revised 2021-08-24
Note: This module should be installed from within Stata by typing "ssc install gridsearch". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
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http://fmwww.bc.edu/repec/bocode/g/gridsearch.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/g/gridsearch.sthlp help file (text/plain)

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