… We prove an inequality on decision trees on monotonic measures which generalizes the
OSSS inequality on product spaces. As an application, we use this inequality to prove a number …

… This paper applies decision tree regression to estimate SM considering different parameters
… of the decision tree regression is an algorithm that generates a decision tree from given …

… use of decision trees, where we apply pruning after reducing the complexity of the the
decision tree using DT-SLIM. Pruning is a method where parts of the decision tree are removed …

… penalised logistic tree regression (PLTR), which uses information from decision trees to
improve the … Formally, rules extracted from various short-depth decision trees built with original …

… This review article aimed to introduce a decision tree for oral white lesions according to their
… In total, more than 20 entities were organized in the form of a decision tree in order to help …

… [6–10] (and others) have shown the possibility of improving the signal significance through
the use of decision tree-based tools, relying on the algorithm to identify the optimal way to …

… decision tree is … decision tree to study the decision-making mechanisms of different piloting
behaviors in order to realize the automatic acquisition and representation of a pilot's decision-…

… We introduce CET, a decision tree that assigns an effective action to an input instance over
the input space. By taking advantage of decision trees, our CET (1) provides a transparent …

… This study introduces the gradient boosted decision tree (GBDT) as a machine learning
approach to circumvent the need for a direct integration of the typically stiff system of ordinary …

… This study estimates a direct ridership model by applying gradient boosting decision trees
to the Metrorail ridership data in the Washington metropolitan area. It addresses the following …