Abstract
A decision tree's classification performance can drop if the tree is used in a changed context such as different accent in speach recognition. This brittleness can partially be rectified by the use of a cheap second tier implemented as a linear classifier. The transfer of the tree to a novel context is accomplished by re-inducing the second tier, without the need to re-induce the more expensive first tier. Experiments reported in this paper indicate that quick adaptation to the target context can indeed be achieved.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 195-204 |
| Number of pages | 10 |
| Journal | Informatica (Ljubljana) |
| Volume | 24 |
| Issue number | 2 |
| State | Published - Jun 1 2000 |
| Externally published | Yes |
ASJC Scopus subject areas
- Software
- Theoretical Computer Science
- Computer Science Applications
- Artificial Intelligence
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Cite this
Kubat, M. (2000). Recycling decision trees in numeric domains. Informatica (Ljubljana), 24(2), 195-204.