The Greedy Prepend Algorithm for Decision List Induction
Deniz Yuret and Michael de la Maza (2006)
( PDF )
- The Greedy Prepend Algorithm for Decision List Induction. In
Proceedings of the 21st International Symposium on Computer and
Information Sciences, ISCIS 2006
We describe a new decision list induction algorithm called the Greedy
Prepend Algorithm (GPA). GPA improves on other decision list
algorithms by introducing a new objective function for rule selection
and a set of novel search algorithms that allow application to large
scale real world problems. GPA achieves state-of-the-art
classification accuracy on the protein secondary structure prediction
problem in bioinformatics and the English part of speech tagging
problem in computational linguistics. For both domains GPA produces a
rule set that human experts find easy to interpret, a marked advantage
in decision support environments. In addition, we compare GPA to
other decision list induction algorithms as well as support vector
machines, C4.5, naive Bayes, and a nearest neighbor method on a number
of standard data sets from the UCI machine learning repository.
- You can download a C implementation of the GPA algorithm with a
Weka interface here.
- Presentation slides are here.