# Are there open-source implementations of stochastic gradient boosting algorithm

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.