Here is a [recently developed] tool for analyzing the choices, risks, objectives, monetary gains, and information needs ...

Deep learning approaches, particularly convolutional neural networks (CNNs) and other architectures, were used in 49 papers. These models excel at image-based tasks such as land cover classification, ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. With the rapid growth of artificial intelligence and machine learning across ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Decision-making during the early stages of research and development (R&D) should be ...

There is indeed a vast literature on the design and analysis of decision tree algorithms that aim at optimizing these parameters. This paper contributes to this important line of research: we propose ...

Abstract: Class imbalance poses a critical challenge in binary classification problems, particularly when rare but significant events are underrepresented in the training set. While traditional ...

Abstract: This research article identifies the fault occurrence in the blowfish cryptography algorithm using a modified Decision Tree classifier. Though there are several cryptography algorithms, the ...

Introduction: The study aims to assess and compare the predictive effectiveness of football-related injuries using external load data and a decision tree classification algorithm by unidimensional ...