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CHAIDFOREST: Stata module to conduct random forest ensemble classification based on chi-square automated interaction detection (CHAID) as base learner

Joseph Luchman ()

Statistical Software Components from Boston College Department of Economics

Abstract: Implements random forest ensemble classifier (Breiman, 2001; Machine Learning) using the CHAID (Chi-square automated interaction detection; Kass, 1980; Applied Statistics) algorithm as the base learner. Includes a module to obtain predicted values from the random forest.

Language: Stata
Requires: Stata version 12.1 and package moremata from SSC (q.v.)
Keywords: random forest; data mining; clustering; machine learning; chi-square; decision tree; exploratory analysis; recursive partitioning; classification (search for similar items in EconPapers)
Date: 2014-11-04, Revised 2015-10-16
Note: This module should be installed from within Stata by typing "ssc install chaidforest". 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/c/chaidforest.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/c/chaidforest_pr.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/c/chaidforest_estat.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/c/chaidforest.sthlp help file (text/plain)
http://fmwww.bc.edu/repec/bocode/c/chaidforest_post.sthlp help file (text/plain)

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