Mathematical Algorithms for Educational Data Classification addresses the critical need for rigorous and transparent methods in educational assessment, where machine learning approaches often lack interpretability despite influencing important educational decisions.
The book bridges advanced mathematical theory with practical application by demonstrating how variational inclusion problems, equilibrium formulations, and iterative algorithms can be applied to educational data classification with provable stability and convergence. Organized into three parts-foundational concepts, iterative algorithms with convergence analysis, and practical case studies-it emphasizes both algorithmic construction and interpretable, equitable results in real educational contexts.
Designed for graduate students, researchers, and professionals in mathematics, learning analytics, and mathematics education, this book serves those seeking both theoretical rigor and actionable methodologies to develop more transparent, equitable, and evidence-based educational decision-making systems.
| ISBN: | 9781041290476 |
| Publication date: | 23rd December 2026 |
| Author: | Nipa Junon |
| Publisher: | CRC Press |
| Format: | Hardback |
| Pagination: | 256 pages |
| Series: | Mathematics and Its Applications |
| Genres: |
Data science and analysis: general Numerical analysis Machine learning Optimization |
Mathematical Algorithms for Educational Data Classification addresses the critical need for rigorous and transparent methods in educational assessment, where machine learning approaches often lack interpretability despite influencing important educational decisions.The book bridges advanced mathematical theory with practical application by demonstrating how variational inclusion problems, equilibrium formulations, and iterative algorithms can be applied to educational data classification with provable stability and convergence. Organized into three parts-foundational concepts, iterative algorithms with convergence analysis, and practical case studies-it emphasizes both algorithmic construction and interpretable, equitable results in real educational contexts.Designed for graduate students, researchers, and professionals in mathematics, learning analytics, and mathematics education, this book serves those seeking both theoretical rigor and actionable methodologies to develop more transparent, equitable, and evidence-based educational decision-making systems.
Mathematical Algorithms for Educational Data Classification features in the following genres: Data science and analysis: general, Numerical analysis, Machine learning, Optimization
Hardback. £93.59, down from the £103.99 cover price. Not Available.
Mathematical Algorithms for Educational Data Classification was written by Nipa Junon and published by CRC Press
Mathematical Algorithms for Educational Data Classification has 256 pages
Yes it is part of Mathematics and Its Applications series
£93.59, reduced from £103.99. Not Available.