• NeC4.5

  • Referenced in 12 articles [sw20994]
  • NeC4.5: Neural Ensemble Based C4.5. Decision tree is with good comprehensibility while neural network ensemble ... novel decision tree algorithm NeC4.5. This algorithm trains a neural network ensemble at first. Then ... trained ensemble and added to the new training set. Finally, a C4.5 decision tree ... network ensemble. Moreover, experiments show that the generalization ability of NeC4.5 decision trees...
  • inTrees

  • Referenced in 6 articles [sw41498]
  • Interpreting Tree Ensembles with inTrees. Tree ensembles such as random forests and boosted trees ... prunes and selects rules from a tree ensemble, and calculates frequent variable interactions. An rule ... learner, referred to as the simplified tree ensemble learner (STEL), can also be formed ... applicable to many types of tree ensembles, e.g., random forests, regularized random forests, and boosted...
  • FastXML

  • Referenced in 8 articles [sw30152]
  • label space. FastXML is an efficient tree ensemble based extreme classifier that can scale ... predictions in milliseconds per test point. Tree ensembles generally require...
  • ranger

  • Referenced in 42 articles [sw14498]
  • high dimensional data. Ensembles of classification, regression and survival trees are supported. We describe...
  • horserule

  • Referenced in 5 articles [sw27913]
  • package horserule: Tree ensembles with rule structured horseshoe regularization. We propose a new Bayesian model ... flexible nonlinear regression and classification using tree ensembles. The model is based on the RuleFit ... where rules from decision trees and linear terms are used in a L1-regularized regression ... trees from Random Forest, which brings a desirable diversity to the ensemble. We sample from...
  • PLANET

  • Referenced in 5 articles [sw15434]
  • Planet: Massively parallel learning of tree ensembles with mapreduce. Classification and regression tree learning ... construction of classification and regression trees, as well as ensembles of such models. We discuss ... using a MapReduce compute cluster for tree learning, and demonstrate the scalability of this approach...
  • BART-BMA

  • Referenced in 5 articles [sw23498]
  • Bayesian version of machine learning tree ensemble methods where the individual trees are the base...
  • Quantregforest

  • Referenced in 6 articles [sw14249]
  • Forests. Quantile Regression Forests is a tree-based ensemble method for estimation of conditional quantiles...
  • BartPy

  • Referenced in 83 articles [sw40584]
  • Bayesian “sum-of-trees” model where each tree is constrained by a regularization prior ... dimensionally adaptive random basis elements. Motivated by ensemble methods in general, and boosting algorithms...
  • CARTscans

  • Referenced in 2 articles [sw20892]
  • including (but not limited to) regression trees, ensembles of trees, and linear regressions with varying...
  • BayesTree

  • Referenced in 64 articles [sw07995]
  • Bayesian “sum-of-trees” model where each tree is constrained by a regularization prior ... dimensionally adaptive random basis elements. Motivated by ensemble methods in general, and boosting algorithms...
  • RADE

  • Referenced in 1 article [sw41100]
  • efficient supervised anomaly detection using decision tree-based ensemble methods. The capability to perform anomaly ... resource consuming, and in particular decision-tree based ensemble classifiers. To address this need ... detection framework that augments standard decision-tree based ensemble classifiers to perform well...
  • OTE

  • Referenced in 1 article [sw33152]
  • package OTE: Optimal Trees Ensembles for Regression, Classification and Class Membership Probability Estimation. Functions ... creating ensembles of optimal trees for regression, classification (Khan, Z., Gul, A., Perperoglou, A., Miftahuddin ... initial set of trees grown by random forest for the ensemble on the basis...
  • OpenDT

  • Referenced in 2 articles [sw12787]
  • Decision Trees; more specifically, an ensemble of decision trees. Machine learning has benefited tremendously from ... speed and in classification accuracy. An ensemble is one such type of multiple classifier system...
  • rocTree

  • Referenced in 2 articles [sw40356]
  • Receiver Operating Characteristic (ROC)-guided survival trees and ensemble algorithms are implemented, providing a unified...
  • SHAFF

  • Referenced in 1 article [sw41806]
  • widely used to interpret both tree ensembles and neural networks, as they can efficiently handle...
  • PyHealth

  • Referenced in 1 article [sw36872]
  • machine learning models, including established ensemble trees and deep neural network-based approaches...
  • overlap

  • Referenced in 1 article [sw34699]
  • data support in each region. Tree ensembles are used to nonparametrically estimate individual causal effects...
  • EIX

  • Referenced in 2 articles [sw35206]
  • this package cover: visualisation of tree-based ensembles models, identification of interactions, measuring of variable...
  • GBMCI

  • Referenced in 2 articles [sw11476]
  • nonparametric model utilizes an ensemble of regression trees to determine how the hazard function varies...