by Joseph Rickert The gradient boosting machine as developed by Friedman, Hastie, Tibshirani and others, has become an extremely successful algorithm for dealing with both classification and regression problems and is now an essential feature of any machine learning toolbox. R’s gbm() function (gbm package) is a particularly well crafted implementation of the gradient boosting machine that served as a model for the rxBTrees() function which was released last year as a feature of Revolution R Enterprise 7.3. You can think of rxBTRees(), as a scaled up version gbm() that is designed to work with massive data sets in distributed...
from R-bloggers http://ift.tt/xdvlrq
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