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

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 ...

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?

To build a decision tree for patients suspected of having prostate cancer using classification and regression tree (CART) analysis.

The Annals of Statistics, Vol. 49, No. 5 (October 2021), pp. 2531-2551 (21 pages) Proposed by Donoho (Ann. Statist. 25 (1997) 1870–1911), Dyadic CART is a nonparametric regression method which ...

AdaBoost.R2 regression sequentially creates an ensemble (collection) of simple decision trees, where each tree is a bit better at prediction than the previous tree. For a given input x, the predicted ...

Course TopicsClassification and regression tree (CART) methods are a class of data mining techniques which constitute an alternative approach to classical regression. CART methods are frequently used ...

To build a decision tree for patients suspected of having prostate cancer using classification and regression tree (CART) analysis.