Improved Machine Learning for Multiclass Fault Classification in Industrial Processes by Khaled Dhibi (16891524)

“…<p dir="ltr">Multiclass fault classification in complex processes is challenging due to many classes, nonlinear dynamics, overlapping fault signatures, and expanding fault taxonomies. …”

A Bayesian Approach to Feature Selection in Classification Problems by Emarly, Maher

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Multiclass feature selection with metaheuristic optimization algorithms: a review by Abu Zitar, Raed

“…Selecting relevant feature subsets is vital in machine learning, and multiclass feature selection is harder to perform since most classifications are binary. …”
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Unified mRNA Subcellular Localization Predictor based on machine learning techniques by Saleh Musleh (15279190)

Neuro-Fuzzy Random Vector Functional Link Neural Network for Classification and Regression Problems by M. Sajid (3070545)

“…Our research involves experiments on various UCI benchmark datasets, covering binary, multiclass classification, and regression tasks. The statistical tests and comprehensive experimental analyses consistently show that all variations of the proposed NF-RVFL model outperform baseline models, highlighting their generalization capabilities. …”

Classification of Cognitive Workload Levels under Vague Visual Stimulation by Mahmoud, Rwan Adil Osman

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Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice by Turker Tuncer (16677966)

Novel Classification System for Classifying Cognitive Workload Levels under Vague Visual Stimulation by Mahmoud, Rwan Adil Osman

“…This is followed by variable selection using stepwise regression and multiclass linear classification. The presented method achieved an average classification accuracy of 93.4%. …”
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Machine Learning-Based Management of Electric Vehicles Charging: Towards Highly-Dispersed Fast Chargers by Mostafa Shibl (18810412)

“…These approaches are chosen as they are classifiers known to have the leading results for multiclass classification problems. The results found shed insight on the importance of the techniques used and their high potential in providing a reliable solution for the coordinated charging of EVs, thus improving the performance of the power grid, and reducing power losses and voltage fluctuations. …”

Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review by Hiba Alzoubi (18001609)

“…Techniques (e.g., model ensembling and multimodal data integration) are needed for better multiclass classification. Further reviews are needed to assess AI's role in other pediatric brain tumors.…”