SECRET: A Scalable Linear Regression Tree Algorithm
SECRET (Scalable EM Classification-based Regression Trees) is a new construction algorithm for regression trees with linear models in the leaves. The algorithm produces regression trees with accuracy comparable to existing algorithms and at the same time requires far less computational effort on large datasets. Experimental results show that SECRET improves the running time of regression tree construction by up to two orders of magnitude compared to previous work while constructing trees of comparable quality.
Source Code Download
The SourceForge download page has instructions on downloading the initial alpha release of the code.
CVS access is also available:
- Browse the source tree hosted at SourceForge: CVS Tree
- Type 'cvs -d:pserver:anonymous@cvs.sourceforge.net:/cvsroot/himalaya-tools login'
- Press Enter when prompted for a password.
- Type 'cvs -z3 -d:pserver:anonymous@cvs.sourceforge.net:/cvsroot/himalaya-tools co Secret'
- A source code tree rooted in a directory called Secret will be created.
Contact
Please send email to 
or contact the authors directly:
Publications
Alin Dobra, Johannes Gehrke.
SECRET: A Scalable Linear Regression Tree Algorithm.
In Proceedings of the Eighth
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
Edmonton, Alberta, Canada, July 2002.