Each technique has pros and cons. This article explains how to implement decision tree regression from scratch, using the C# language. Compared to other regression techniques, decision tree regression ...

Several approaches can be taken to predict case membership in the classes of a dependent variable. Classification and regression trees (CART) analysis has been cited repeatedly as a powerful ...

Sabyasachi Chatterjee, Subhajit Goswami, ADAPTIVE ESTIMATION OF MULTIVARIATE PIECEWISE POLYNOMIALS AND BOUNDED VARIATION FUNCTIONS BY OPTIMAL DECISION TREES, The Annals of Statistics, Vol. 49, No. 5 ...

More questions: Decision Trees: What are the advantages of using a decision tree for classification? Classification: Why is the output of logistic regression interpreted as a probability?

Decision tree accuracy is typically measured by metrics like classification accuracy (for classification tasks), or Mean Squared Error/R-squared (for regression tasks).

Classification and Regression Trees (CART) Course Topics Classification and regression tree (CART) methods are a class of data mining techniques which constitute an alternative approach to classical ...

Clarification and regression tree analysis can be easily applied to health risk assessment data, thus providing HMO decision makers with more sensitive estimates of cost risk than those based on ...

Regression trees are applied to evaluate system performance – using two water quality and two economic performance metrics. Regression trees facilitated insights into the significance of uncertain ...