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 ...

What are the advantages of logistic regression over decision trees? This question was originally answered on Quora by Claudia Perlich.

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

For more information on this research see: Comparison and Analysis of the Effectiveness of Linear Regression, Decision Tree, and Random Forest Models for Health Insurance Premium Forecasting.

A random forest is an ensemble of a large number of classification or regression trees (also known as decision trees). Regression tree algorithms sort observations. The word observation in this ...

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 ...

To investigate how students' characteristics and experiences affect satisfaction, this study uses regression and decision tree analysis with the CHAID algorithm to analyze student-opinion data. A data ...

Unlike regression models that yield parameter estimates, the decision tree results, once tabulated and depicted, are simple to interpret and use.

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 ...