Are there open-source implementations of stochastic gradient boosting algorithm |
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described in
Friedman, Jerome H. (1999a). Greedy Function Approximation: A Gradient Boosting Machine. Technical report, Dept. of Statistics, Stanford University.
Friedman, Jerome H. (1999b). Stochastic Gradient Boosting. Technical report, Dept. of Statistics, Stanford University.
Ramasubbu Venkatesh answers:
Weka and R may be good open source packages to explore.
For example, take a look at the
gbm package in R, described in
Ridgeway, G. (2005). "Generalized Boosted Models: A guide to the gbm package,"
(i-pensieri.com/gregr/papers/gbm-vignette.pdf).
Additive Regression,a WEKA metaclassifier may also be of interest.
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