Abstract
We examine a new approach to building decision tree by introducing a geometric splitting criterion, based on the properties of a family of metrics on the space of partitions of a finite set. This criterion can be adapted to the characteristics of the data sets and the needs of the users and yields decision trees that have smaller sizes and fewer leaves than the trees built with standard methods and have comparable or better accuracy.
| Original language | English |
|---|---|
| Pages (from-to) | 239-256 |
| Number of pages | 18 |
| Journal | International Journal of Parallel, Emergent and Distributed Systems |
| Volume | 21 |
| Issue number | 4 |
| DOIs | |
| State | Published - Aug 1 2006 |
ASJC Scopus Subject Areas
- Software
- Computer Networks and Communications
Keywords
- Decision tree
- Generalized conditional entropy
- Metric
- Metric betweenness
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