LOTUS version 2.3
LOTUS is a logistic regression tree algorithm developed by Kin-Yee Chan and Wei-Yin Loh (University of Wisconsin-Madison).
LOTUS is unique among logistic regression tree algorithms in possessing the following features:
Negligible bias in variable selection (very important for tree interpretation); Ability to use ordered (continuous) and unordered (categorical) predictor variables; Choice of roles for predictor variables (splitting only, node modeling only, both, or none); Choice of piecewise best simple linear, multiple linear or stepwise logistic regression models; Choice of stopping rules: pruning by cross-validation or prunning with a test sample; Automatic handling of missing values; Automatic generation of LaTeX (MikTeX) or allCLEAR source code for the tree diagrams. The LaTeX code requires the PSTricks package.
Compiled binaries: The following files are freely distributed for non-profit use only.
Intel and compatibles (Windows 9x/NT/2000/XP) in winzip format --- download Intel and compatibles (Linux 2.4 or later) in gzip format --- download
Revision history: See the file history.txt
Related tree algorithms with unbiased selection:
GUIDE: A piecewise-linear least-squares, quantile and Poisson regression tree CRUISE: A classification tree that splits each node into two or more subnodes QUEST: A classification tree restricted to binary splits
Last updated: May 11, 2013 by W.-Y. Loh
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