Combining logistic regression and decision trees: An application to industrial steel data Skip to
main content Salford University Repository Home Research Outputs People Schools Research …

Regression Trees | SpringerLink Skip to main content Advertisement SpringerLink Account
Menu Find a journal Publish with us Track your research Search Cart Book cover Effective …

Decision trees can be used both for predictive modeling in classification and regression
contexts and for variable selection for use with other modeling procedures. The primary goal …

Suppose one had a single quantitative response variable and several predictors. There is
interest in y| x. The task is to find the single best predictor. To do this, two kinds of searches …

Two ensemble methods are considered in this chapter, namely bagging trees and random
forests. One issue with regression trees is their high variance. There is a high variability of …

The TREES module computes classification and regression trees. Classification trees
include those models in which the dependent variable (the predicted variable) is categorical …

Tree based methods in S or R are extremely useful and popular. For simple trees and
memorable variables it is easy to predict the outcome for a new case using only a standard …

Classification and Regression Tree Methods Page 1 Classification and Regression Tree
Methods (In Encyclopedia of Statistics in Quality and Reliability, Ruggeri, Kenett and Faltin (eds.) …

This chapter discusses Classification and Regression Trees, widely used in data mining for
predictive analytics. The chapter starts by explaining the two principal types of decision …