Abstract
In the paper, we study a greedy algorithm for construction of approximate decision trees. This algorithm is applicable to decision tables with many-valued decisions where each row is labeled with a set of decisions. For a given row, we should find a decision from the set attached to this row.We use an uncertainty measure which is the number of boundary subtables. We present also experimental results for data sets from UCI Machine Learning Repository for proposed approach and approach based on generalized decision.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 13-24 |
| Number of pages | 12 |
| Journal | CEUR Workshop Proceedings |
| Volume | 928 |
| State | Published - 2012 |
| Event | 21th International Workshop on Concurrency, Specification and Programming, CS and P 2012 - Berlin, Germany Duration: Sep 26 2012 → Sep 28 2012 |
Keywords
- Decision table with many-valued decisions
- Decision tree
- Greedy algorithm
ASJC Scopus subject areas
- General Computer Science