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| Content Provider | Springer Nature Link |
|---|---|
| Author | Kotsiantis, S. B. |
| Copyright Year | 2011 |
| Abstract | Decision tree techniques have been widely used to build classification models as such models closely resemble human reasoning and are easy to understand. This paper describes basic decision tree issues and current research points. Of course, a single article cannot be a complete review of all algorithms (also known induction classification trees), yet we hope that the references cited will cover the major theoretical issues, guiding the researcher in interesting research directions and suggesting possible bias combinations that have yet to be explored. |
| Starting Page | 261 |
| Ending Page | 283 |
| Page Count | 23 |
| File Format | |
| ISSN | 02692821 |
| Journal | Artificial Intelligence Review |
| Volume Number | 39 |
| Issue Number | 4 |
| e-ISSN | 15737462 |
| Language | English |
| Publisher | Springer Netherlands |
| Publisher Date | 2011-06-29 |
| Publisher Place | Dordrecht |
| Access Restriction | Subscribed |
| Subject Keyword | Machine learning Decision trees Classification algorithms Artificial Intelligence (incl. Robotics) Computer Science |
| Content Type | Text |
| Resource Type | Article |
| Subject | Artificial Intelligence Linguistics and Language |
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