Forests of Fuzzy Decision Trees
Overview & Synopsis
In inductive learning, to build decision trees is often arduous when there exists more than two classes to learn. In this paper, a method of decomposition of problems with more than two classes into several problems with only two classes is proposed. This decomposition enables the construction of a forest of fuzzy decision trees where each fuzzy decision tree is dedicated to the recognition of a single class against a combination of all the other classes. The construction of fuzzy decision trees is based on an extension of the ID3 algorithm which handles imprecision in data. A method to use such a forest of fuzzy decision trees to classify new cases is also proposed.
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Document Information
| Document Title | Forests of Fuzzy Decision Trees |
|---|---|
| Author / Organization | Christophe Marsala, Bernadette Bouchon-Meunier |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 1997 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-183466 |
| Original Source Link | Visit Source Page on hal.science » |