Machine learning models and dimensionality reduction for improving the Android malware detection by Pablo Morán, Antonio Robles-Gómez, Andres Duque, Llanos Tobarra, Rafael Pastor-Vargas

“…This work first proposes a new efficient dimensionality reduction of features, as well as the application of several supervised machine learning algorithms for prediction purposes. …”
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Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, Salama Mostafa

“…The present study proposes an efficient DDoS attack detection model. This model relies mainly on dimensionality reduction and machine learning algorithms. …”
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Physics-informed machine learning for automatic model reduction in chemical reaction networks by Joseph Pateras, Colin Zhang, Shriya Majumdar, Ayush Pal, Preetam Ghosh

“…Abstract Physics-informed machine learning bridges the gap between the high fidelity of mechanistic models and the adaptive insights of artificial intelligence. …”
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Evaluating the Effectiveness of Dimensionality Reduction on Machine Learning Algorithms in Time Series Forecasting by Rida Zaheer, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Ramzan Talib

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Reactor physics fast calculation method based on model order reduction and machine learning by Chen Zhao, Qinyi Zhang, Bin Zhang, Jiangyu Wang, Jiayi Liu, Lianjie Wang, Bangyang Xia, Xiaoming Chai, Xingjie Peng

Subjects: “…Model order reduction…”
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Educational improvement through machine learning: Strategic models for better PISA scores. by Bilal Baris Alkan, Serafettin Kuzucuk, Şevki Yetkin Odabasi, Leyla Karakuş

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Machine Learning Approaches for Real-Time Mineral Classification and Educational Applications by Paraskevas Tsangaratos, Ioanna Ilia, Nikolaos Spanoudakis, Georgios Karageorgiou, Maria Perraki

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Model Complexity Reduction for ZKML Healthcare applications by Sathya Krishnasamy, Ilangovan Govindarajan

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Interactive Mitigation of Biases in Machine Learning Models for Undergraduate Student Admissions by Kelly Van Busum, Shiaofen Fang

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Unsupervised Machine Learning Approaches for Test Suite Reduction by Anila Sebastian, Hira Naseem, Cagatay Catal

“…Over the past decade, machine learning-based solutions have emerged, demonstrating remarkable effectiveness and efficiency. …”
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Fatigue damage reduction in hydropower startups with machine learning by Till Muser, Ekaterina Krymova, Alessandro Morabito, Martin Seydoux, Elena Vagnoni

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Interpretable Machine Learning Models for PISA Results in Mathematics by Ismael Gomez-Talal, Luis Bote-Curiel, Jose Luis Rojo-Alvarez

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Detection of Alzheimer’s Disease using Explainable Machine Learning and Mathematical Models by Krishna Mahapatra, R. Selvakumar

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Near viewing behaviors predict educational system in a machine learning model by Ravid Doron, Einat Shneor, Lisa A. Ostrin, Ariela Gordon-Shaag, Ayelet Goldstein

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Predicting practical reduction potential of electrolyte solvents via computational hydrogen electrode and interpretable machine-learning models by Zonglin Yi, Yi Zhou, Hao Liu, Li Li, Yan Zhao, Jiayuan Li, Yixuan Mao, Fangyuan Su, Cheng-Meng Chen

“…Machine-learning models are trained based on the organic and inorganic electrolyte solvents that possess experimentally identified reduction mechanisms. …”
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Machine Learning and Generative AI in Learning Analytics for Higher Education: A Systematic Review of Models, Trends, and Challenges by Miguel Ángel Rodríguez-Ortiz, Pedro C. Santana-Mancilla, Luis E. Anido-Rifón

“…This systematic review examines how machine learning (ML) and generative AI (GenAI) have been integrated into learning analytics (LA) in higher education (2018–2025). …”
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Fair and Transparent Student Admission Prediction Using Machine Learning Models by George Raftopoulos, Gregory Davrazos, Sotiris Kotsiantis

“…This paper explores the development and evaluation of machine learning models designed to predict student admissions while prioritizing fairness and interpretability. …”
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Opportunities of machine learning algorithms for education by Olga Ovtšarenko

“…The results suggest potential applications in personalized course recommendations, prediction and dropout prevention strategies, resulting in a more effective and personalized educational experience. Future research will focus on improving models of available registration data, exploring and using advanced machine learning techniques to improve the accuracy and usefulness of predictions, and providing faster recommendations to help students navigate their studies more effectively.…”
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Ensemble machine learning for predicting academic performance in STEM education by Aklilu Mandefro Messele

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Reduction of monoclonal antibody viscosity using interpretable machine learning by Emily K. Makowski, Hsin-Ting Chen, Tiexin Wang, Lina Wu, Jie Huang, Marissa Mock, Patrick Underhill, Emma Pelegri-O’Day, Erick Maglalang, Dwight Winters, Peter M. Tessier

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