I am new to decision tree method. For decision tree regression model, does it just fit a piece wise step function over data? When and why would people prefer it over some traditional regression like locally weighted (LOESS) regression?
Topic decision-trees regression
Category Data Science
There are two important differences between decision trees and regression:
Decision tree fit a straight a line (mean of the dependent variable for the feature space). Regression fits a sloped line (rise over run).
Decision trees typically do not predict values outside the observed range. Linear regression can predict values outside the observed range.
Geeks Mental is a community that publishes articles and tutorials about Web, Android, Data Science, new techniques and Linux security.