We analyze the performance of top down algorithms for decision tree learning, such as those employed by the widely used C4.5 and CART software packages. Our main result is a proof that such algorithms are boosting algorithms. By this we mean that if the functions that label the internal nodes of the
β¦ LIBER β¦
On the generalization ability of on-line learning algorithms
β Scribed by Cesa-Bianchi, N.; Conconi, A.; Gentile, C.
- Book ID
- 114638411
- Publisher
- IEEE
- Year
- 2004
- Tongue
- English
- Weight
- 213 KB
- Volume
- 50
- Category
- Article
- ISSN
- 0018-9448
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