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 ...

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

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 ...

There are roughly a dozen major regression techniques, and each technique has several variations. Among the most common techniques are linear regression, linear ridge regression, k-nearest neighbors ...

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 ...

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?

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 ...

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 ...