Decision trees are interpretable supervised learning algorithms used for classification and regression tasks. (33) When predicting LCI data on the level of technical flows, the target values are ...

Abstract Decision tree is an effective supervised learning method for solving classification and regression problems. This article combines the Pearson correlation coefficient with the CART decision ...

Using MaxSAT for Efficient Explanations of Tree Ensembles (AAAI 2022) Alexey Ignatiev, Yacine Izza, Peter J. Stuckey, João Marques-Silva [Paper] FOCUS: Flexible Optimizable Counterfactual Explanations ...

ID3 decision tree is the most extensive method. It can be used to classify, identify and predict data information, and the whole system can be divided into several stages according to its nature. It ...

Decision trees are a popular machine learning algorithm that can be used for both classification and regression tasks. They operate by recursively dividing the dataset into subsets according to the ...

A decision tree is a machine learning technique that can be used for binary classification or multi-class classification. A binary classification problem is one where the goal is to predict the value ...

The traditional decision tree algorithm has an over-fitting phenomenon and its pruning step is time-consuming. It is difficult to meet the actual needs in classifying bank customers. In response to ...

While Markov Chain Monte Carlo methods are typically used to construct Bayesian Decision Trees, here we provide a deterministic Bayesian Decision Tree algorithm that eliminates the sampling and does ...