• randomForest

  • Referenced in 144 articles [sw10639]
  • package randomForest: Breiman and Cutler’s random forests for classification and regression. Classification and regression ... based on a forest of trees using random inputs...
  • GeneSrF

  • Referenced in 62 articles [sw08254]
  • GeneSrF: gene selection with random forests (v. 20070524). GeneSrF is a web tool for gene ... selection in classification problems that uses random forest. Two approaches for gene selection are used...
  • SPOT

  • Referenced in 74 articles [sw06347]
  • based models such as CART and random forest; Gaussian process models (Kriging), and combinations...
  • pSuc-Lys

  • Referenced in 31 articles [sw16643]
  • proteins with PseAAC and ensemble random forest approach. Being one type of post-translational modifications ... balancing out skewed training dataset by random sampling, and (3) constructing an ensemble predictor ... fusing a series of individual random forest classifiers. Rigorous cross-validations indicated that it remarkably...
  • missForest

  • Referenced in 24 articles [sw19483]
  • missForest: Nonparametric Missing Value Imputation using Random Forest. The function ’missForest’ in this package ... mixed-type data. It uses a random forest trained on the observed values...
  • AFP-Pred

  • Referenced in 24 articles [sw22441]
  • Pred: A random forest approach for predicting antifreeze proteins from sequence-derived properties. Some creatures ... this work, we report a random forest approach ”AFP-Pred” for the prediction of antifreeze...
  • randomSurvivalForest

  • Referenced in 23 articles [sw08133]
  • randomSurvivalForest: Random Survival Forests. Random survival forests for right-censored and competing risks survival data...
  • iPPI-Esml

  • Referenced in 26 articles [sw22413]
  • classifier formed by fusing seven individual random forest engines via a voting system...
  • iPTM-mLys

  • Referenced in 26 articles [sw23948]
  • fusing an array of basic random forest classifiers into an ensemble system. Rigorous cross-validations...
  • party

  • Referenced in 25 articles [sw07330]
  • provides an implementation of Breiman’s random forests. The function mob() implements an algorithm...
  • ranger

  • Referenced in 15 articles [sw14498]
  • ranger: A Fast Implementation of Random Forests for High Dimensional Data ... software is a fast implementation of random forests for high dimensional data. Ensembles of classification ... most memory efficient implementation of random forests to analyze data on the scale...
  • iDNA-Prot

  • Referenced in 16 articles [sw22410]
  • identification of DNA binding proteins using random forest with grey model. DNA-binding proteins play ... grey model” and by adopting the random forest operation engine, we proposed a new predictor...
  • iPhos-PseEvo

  • Referenced in 17 articles [sw23953]
  • fusing an array of individual random forest classifiers thru a voting system. Rigorous jackknife tests...
  • iHyd-PseCp

  • Referenced in 15 articles [sw23952]
  • acid composition (PseAAC) and introducing the ”Random Forest” algorithm to operate the calculation. Rigorous jackknife...
  • iRNA-2methyl

  • Referenced in 14 articles [sw24530]
  • composition), followed by fusing 12 basic random forest classifier into four ensemble predictors, with each...
  • varSelRF

  • Referenced in 8 articles [sw08253]
  • package varSelRF: Variable selection using random forests. Variable selection from random forests using both backwards...
  • randomForestSRC

  • Referenced in 6 articles [sw14394]
  • randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC). A unified treatment of Breiman ... random forests for survival, regression and classification problems based on Ishwaran and Kogalur’s random...
  • iDHS-EL

  • Referenced in 10 articles [sw22426]
  • formed by fusing three individual Random Forest (RF) classifiers into an ensemble predictor. The three...
  • PREvaIL

  • Referenced in 10 articles [sw25073]
  • residue-contact network, in a random forest machine-learning framework. Extensive benchmarking experiments on eight...
  • iPPI-PseAAC

  • Referenced in 9 articles [sw27665]
  • used in this predictor is the random forests algorithm. It has been observed...