ODA: Stata module for conducting Optimal Discriminant Analysis (Windows only)

Ariel Linden

Statistical Software Components from Boston College Department of Economics

Abstract: Optimal discriminant analysis is a machine learning algorithm that was introduced over 30 years ago to offer an alternative analytic approach to conventional statistical methods commonly used in research (Yarnold & Soltysik 1991). Its appeal lies in its simplicity, flexibility and accuracy as compared with conventional statistical methods (Yarnold & Soltysik 2005, 2016). Given classvar (2 or more distinct levels) and attrvar (continuous, or categorical via cat), oda performs an exhaustive search for the cutpoint, the optimal category grouping, the optimal ordered segmentation, or the optimal per-category class assignment that maximizes classification accuracy, and reports overall accuracy, PAC (Percent Accuracy in Classification) and PV (Predictive Value) for every class, and their corresponding Effect Strength (ESS) measures. oda extends ODA's original functionality in a number of ways -- most notably bootstrap confidence intervals and a significance test on the leave-one-out table for a multi-category classvar (looreps()).

Language: Stata
Requires: Stata version 14 for Windows and purchase of ODA software
Keywords: machine learning; data mining; Discriminant analysis; Classification analysis (search for similar items in EconPapers)
Date: 2020-01-12, Revised 2020-09-09
Note: This module should be installed from within Stata by typing "ssc install oda". 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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Downloads: (external link)
http://fmwww.bc.edu/repec/bocode/o/oda.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/o/oda_predict.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/o/oda.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/o/ODA_tech_suppl.pdf

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Persistent link: https://EconPapers.repec.org/RePEc:boc:bocode:s458728

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