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 ...

If the signal to noise ratio is low (it is a ‘hard’ problem) logistic regression is likely to perform best. In technical terms, if the AUC of the best model is below 0.8, logistic very clearly ...

In the so-called explained artificial intelligence, there is a need to build small models, but accurate and intuitive for the analyst. It is necessary to formalize, which models are perceived by ...

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 ...

The AdaBoost.R2 regression algorithm has not received as much research attention as other tree-based regression ensemble techniques such as random forest regression, ... It's quite possible that an ...

The paper introduces the PILOT learning algorithm for constructing linear model trees, enhancing decision tree interpretability and performance. It uses a standard regression model with centered ...