Abstract Decision trees are a widely used method for classification, both alone and as the building blocks of multiple different ensemble learning methods. The Max Cut decision tree introduced here involves novel modifications to standard, baseline variant classification tree, CART Gini. One modification an alternative splitting metric, Cut, based on maximizing distance between all pairs observ...

Decision tree classification procedures have been largely overlooked in remote sensing applications. In this paper we compare the classification performance of three types of decision trees across three different data sets. The classifiers that are considered include a univariate decision tree, multivariate decision tree, and a hybrid decision tree. Results from an n-fold cross-validation proce...

results overall, the prevalence of unwanted pregnancies was 32.3%. the performance of the models based on the area under the roc curve as the indicator was as follows: artificial neural networks (0.741), decision tree (0.731), and logistic regression (0.712). the highest sensitivity level belonged to the decision tree (73.5%), and the highest specificity level belonged to the artificial neural ...

Nitrogen is produced mainly from its most abundant source, the air, using three processes: membrane, pressure swing adsorption (PSA) and cryogenic. The most common method for evaluating a process is using the selection diagrams based on feasibility studies. Since the selection diagrams are presented by different companies, they are biased, and provide unsimilar and even controversial results. I...

Introduction: Attention-Deficit/Hyperactivity Disorder (ADHD) is a well-known neurodevelopmental disorder. Diagnosis and treatment of ADHD can often lead to a developmental trajectory toward positive results. The present study aimed at implementing the decision tree method to recognize children with and without ADHD, as well as ADHD subtypes.  Methods: In the present study, the subjects includ...

To avoid checking unnecessary or irrelevant conditions of rules, the irrelevant values problem of the decision tree is addressed. We propose an algorithm to remove irrelevant conditions of rules in the process of converting the decision tree to rules according to the semantics of the decision tree. Since our algorithm depends only on the semantics of the decision tree, our algorithm can be inte...