July 2019
Beginner to intermediate
298 pages
7h 20m
English
Content preview from Hands-On Ensemble Learning with Python
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Further reading
As this is a hands-on book, we will not go further into the mathematical aspect of the algorithm. Nonetheless, for the mathematically curious or inclined, we recommend the following papers. The first is a more regression-specific framework, while the second is more general:
- Friedman, J.H., 2001. Greedy function approximation: a gradient boosting machine. Annals of statistics, pp.1189-1232.
- Mason, L., Baxter, J., Bartlett, P.L. and Frean, M.R., 2000. Boosting algorithms as gradient descent. In Advances in neural information processing systems (pp. 512-518).
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