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 ...

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 ...

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 ...

Decision Tree: A single decision tree structure used in making decisions based on features of the dataset. Random Forest: An ensemble of multiple decision trees that combine the output for improved ...

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 ...