Results 41 to 50 of about 85,077 (292)
Optimization of decision trees using modified African buffalo algorithm
Journal of King Saud University: Computer and Information Sciences, 2022 Decision tree induction is a simple, however powerful learning and classification tool to discover knowledge from the database. The volume of data in databases is growing to quite large sizes, both in the number of attributes and instances.
Archana R. Panhalkar, Dharmpal D. Doye
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End-to-End Learning of Deterministic Decision Trees [PDF]
, 2019 Conventional decision trees have a number of favorable properties, including interpretability, a small computational footprint and the ability to learn from little training data. However, they lack a key quality that has helped fuel the deep learning revolution: that of being end-to-end trainable, and to learn from scratch those features that best ...
Fred A. Hamprecht, Thomas M. Hehn
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Heat demand prediction: A real-life data model vs simulated data model comparison
Energy Reports, 2021 In the recent years machine learning algorithms have developed further and various applications are taking advantage of this advancement. Modern machine learning is now used in district heating for more precise and realistic heat demand prediction ...
Kevin Naik, Anton Ianakiev
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IEEE Access, 2021 This paper presents the synthesis of multiband frequency selective surfaces (FSSs) using supervised machine learning (ML) with the decision tree (DT) algorithm.
Leidiane C. M. M. Fontoura +4 more
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Global Evaluation for Decision Tree Learning
, 2022 We transfer distances on clusterings to the building process of decision trees, and as a consequence extend the classical ID3 algorithm to perform modifications based on the global distance of the tree to the ground truth--instead of considering single leaves.
Spaeh, Fabian, Kosub, Sven
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Computers and Education: Artificial Intelligence, 2021 In the area of machine learning and data science, decision tree learning is considered as one of the most popular classification techniques. Therefore, a decision tree algorithm generates a classification and predictive model, which is simple to ...
Vasiliki Matzavela, Efthimios Alepis
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Complexity, 2020 Software defects prediction at the initial period of the software development life cycle remains a critical and important assignment. Defect prediction and correctness leads to the assurance of the quality of software systems and has remained integral to
Rashid Naseem +6 more
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Machine Learning in Injection Molding: An Industry 4.0 Method of Quality Prediction
Sensors, 2022 One of the essential requirements of injection molding is to ensure the stable quality of the parts produced. However, numerous processing conditions, which are often interrelated in quite a complex way, make this challenging.
Richárd Dominik Párizs +3 more
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Applying Machine Learning Techniques to the Audit of Antimicrobial Prophylaxis
Applied Sciences, 2022 High rates of inappropriate use of surgical antimicrobial prophylaxis were reported in many countries. Auditing the prophylactic antimicrobial use in enormous medical records by manual review is labor-intensive and time-consuming.
Zhi-Yuan Shi +4 more
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Molecular Oncology, EarlyView.Circulating tumor DNA (ctDNA) offers a possibility for different applications in early and late stage breast cancer management. In early breast cancer tumor informed approaches are increasingly used for detecting molecular residual disease (MRD) and early recurrence. In advanced stage, ctDNA provides a possibility for monitoring disease progression and
Eva Valentina Klocker +14 more
wiley +1 more source