Advanced predictive algorithms and analytics

So far, we have examined the data preparation and data exploration functions available in the RevoScaleR package. Besides these functions, predicting classification or regression problems can also be done, especially when dealing with large datasets.

I will mention only few of these. The complete list is available online (https://docs.microsoft.com/en-us/machine-learning-server/r-reference/revoscaler/revoscaler) and some of the points are as follows:

• rxLinMod: This is used for building and predicting a linear model
• rxLogit: This is used for building and predicting the logistic regression model
• rxGlm: This is used for creating a generalized linear model
• rxDTree: This is used for creating a classification or regression tree
• rxBTrees: This is used for building a classification or regression decision forest—that is using a stochastic gradient boosting algorithm
• rxDForest: This is used for building a classification or regression decision forest model
• rxNaiveBayes...