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alternative algorithm using alternative algorithm the classification template uses the naive bayes algorithm by default. you can easily add and use other mllib classification algorithms. the following will demonstrate how to add the mllib random forests algorithm into the engine. you can find the complete modified

usage of these parameters. modify the naivebayesalgorithm class to randomforestalgorithm. the changes are: the new randomforestalgorithmparams class is used as parameter. randomforestmodel is used in type parameter. this is the model returned by the random forest algorithm. the train() function is modified...

http://predictionio.apache.org/templates/classification/add-algorithm/

exclude some items from recommendation (for example, in the browsing session, the user just added some items to shopping cart, or you have a list of items you want to filter out, you may want to supply blacklist in query). this how-to will demonstrate how you can do it. you can find the complete modified

recommendproductswithfilter() returns array[mllibrating], which uses item int // index. convert it to string id for returning predictedresult val blacklist = query.blacklist.flatmap(model.itemstringintmap.get) // added val itemscores = model .recommendproductswithfilter(userint, query.num, blacklist) // modified...

http://predictionio.apache.org/templates/recommendation/blacklist-items/