• CORElearn

  • Referenced in 5 articles [sw10624]
  • regression, for example classification and regression trees with optional constructive induction and models ... forests, kNN, naive Bayes, and locally weighted regression. It is especially strong in feature evaluation...
  • VBayesLab

  • Referenced in 5 articles [sw41752]
  • statistical literature, the Bayesian additive regression trees (BART) method. User-friendly software packages in Matlab...
  • MedTree

  • Referenced in 3 articles [sw12469]
  • novel algorithm to optimize classification trees. L. Breiman, J. H. Friedman, R. A. Olshen ... Stone [Classification and regression trees (1984; Zbl 0541.62042)] expounded a method called classification and regression ... trees, or CART, which is of use for nonparametric discrimination and regression. In this paper ... able to increase the quality of classification trees beyond the quality of trees, which...
  • dynaTree

  • Referenced in 4 articles [sw07923]
  • sequential Monte Carlo for dynamic tree regression and classification models with hooks provided for sequential ... inputs. Illustrative examples from the original dynamic trees paper are facilitated by demos...
  • HHCART

  • Referenced in 4 articles [sw38489]
  • HHCART: an oblique decision tree. Decision trees are a popular technique in statistical data classification ... particular class. The basic Classification and Regression Tree (CART) algorithm partitions the feature space using...
  • CARTopt

  • Referenced in 4 articles [sw08364]
  • using classification and regression trees (CART) from statistical pattern recognition. The CART partition defines desirable...
  • ofw

  • Referenced in 4 articles [sw10549]
  • multiclass classifiers such as classification and regression trees and support vector machines. Furthermore, a weighted...
  • glmtree

  • Referenced in 2 articles [sw33576]
  • package glmtree: Logistic Regression Trees. A logistic regression tree is a decision tree with logistic ... regressions at its leaves. A particular stochastic expectation maximization algorithm is used to draw ... good trees, that are then assessed via the user’s criterion of choice among...
  • bartCause

  • Referenced in 2 articles [sw40926]
  • bartCause: Causal Inference using Bayesian Additive Regression Trees. Contains a variety of methods to generate ... causal inference estimates using Bayesian Additive Regression Trees (BART) as the underlying regression model (Hill...
  • partDSA

  • Referenced in 2 articles [sw07441]
  • such methods are Classification and Regression Trees (CART) and a more recent competitor known ... differ in the manner by which regression trees are constructed. Recently, we have shown that...
  • CARTscans

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

  • Referenced in 2 articles [sw31423]
  • /jcgs.2010.06089>, integrating a regression tree and a multiple regression model...
  • horserule

  • Referenced in 5 articles [sw27913]
  • package horserule: Tree ensembles with rule structured horseshoe regularization. We propose ... Bayesian model for flexible nonlinear regression and classification using tree ensembles. The model is based ... from decision trees and linear terms are used in a L1-regularized regression. We modify ... RuleFit with an additional set of trees from Random Forest, which brings a desirable diversity...
  • gbev

  • Referenced in 1 article [sw16487]
  • package gbev: Gradient boosted regression trees with errors-in-variables. This package performs non-parametric ... models are estimated using gradient boosted regression trees. Regression is performed using squared error loss...
  • meta-CART

  • Referenced in 1 article [sw27451]
  • approach that applies classification and regression trees (CART) to identify interactions, and then subgroup meta ... their accuracy, and using a regression tree to avoid dichotomization. In addition, new pruning rules ... simulation results revealed that meta-regression trees with random-effects weights and a 0.5-standard...
  • maptree

  • Referenced in 2 articles [sw12946]
  • package maptree: Mapping, pruning, and graphing tree models. Functions with example data for graphing, pruning ... from hierarchical clustering, and classification and regression trees...
  • mBART

  • Referenced in 2 articles [sw41499]
  • nonparametric nature of BART (Bayesian Additive Regression Trees) allows for a much richer...
  • GBMCI

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

  • Referenced in 1 article [sw27008]
  • classification trees as well as for regression trees. However, the use of the novel testing ... approach has not been tested for regression trees so far, so this routine is meant...
  • semibart

  • Referenced in 1 article [sw31324]
  • semiparametric modeling approach using Bayesian additive regression trees with an application to evaluate heterogeneous treatment ... effects. Bayesian Additive Regression Trees (BART) is a flexible machine learning algorithm capable of capturing ... covariates. We extend BART to a semiparametric regression framework in which the conditional expectation...