R Graphical Manual

Last data update: 2014.03.03

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drandomForest (Package: randomForest.ddR) : Distributed randomForest with parallelism in sub-forest level

drandomForest function runs randomForest function of randomForest package in a distributed fashion with parallelism in sub-forest level. drandomForest calls several instances of randomForest distributed across a cluster system in order to create sub-forests concurrently. Therefore, the master distributes the input data among all R-executors of the distributedR environment, and trees on different sub-sections of the forest are created simultaneously. At the end, all these trees are combined to result a single forest.

● Data Source: CranContrib
● Keywords: Big Data Analytics, distributed R, distributed random forest
● Alias: drandomForest, drandomForest.default, drandomForest.formula
● 0 images

randomForest.ddR-package (Package: randomForest.ddR) : distributed version of randomForest package

randomForest.ddR leverages the randomForest package to provide a parallel training and prediction function

● Data Source: CranContrib
● Keywords: Big Data Analytics, Scalable Machine Learning algorithms
● Alias: randomForest.ddR, randomForest.ddR-package
● 0 images

predict.drandomForest (Package: randomForest.ddR) : distributed predict method for applying a random forest objects on a darray or a dframe

This function can be used to apply a model of type drandomForest or randomForest to a new data for prediction.

● Data Source: CranContrib
● Keywords: classification, regression
● Alias: predict.drandomForest
● 0 images