{ "_id": "6a1eb09ab25058d4daadb91e", "Package": "Dforest", "Type": "Package", "Title": "Decision Forest", "Version": "0.4.2", "Date": "2017-11-28", "Author": "Leihong Wu , Weida Tong\n(Weida.tong@fda.hhs.gov)", "Maintainer": "Leihong Wu ", "Description": "Provides R-implementation of Decision forest algorithm,\nwhich combines the predictions of multiple independent decision\ntree models for a consensus decision. In particular, Decision\nForest is a novel pattern-recognition method which can be used\nto analyze: (1) DNA microarray data; (2) Surface-Enhanced Laser\nDesorption/Ionization Time-of-Flight Mass Spectrometry\n(SELDI-TOF-MS) data; and (3) Structure-Activity Relation (SAR)\ndata. In this package, three fundamental functions are\nprovided, as (1)DF_train, (2)DF_pred, and (3)DF_CV. run\nDforest() to see more instructions. 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