A Decision Tree Regressor is a machine learning algorithm used for regression tasks, where the goal is to predict a continuous target variable. Decision Trees work by recursively partitioning the ...

An implementation of decision trees for regression and classification which handle categorical and continuous features. The algorithms are tested on the notorious Titanic and Iris datasets. The ...

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

The formal definition of the complementarities of the feathers is proposed. Algorithm of building regression decision tree with complementary features is presented. Condition of plausibility of ...

The objective of the research study is to predict and analyze the flight ticket fare using machine learning algorithm Random Forest Regressor in comparison with Decision tree Regression algorithm. The ...

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 ...

Researchers from The University of Antwerp and KU Leuven have explored decision trees like CART and C4.5, which are popular for quick training and interpretability. They found classical regression ...