Books Pages

Analysis and Optimization of Decision and Inhibitory Trees, Rules, and Tests (initiative project)

Design and analysis of greedy algorithms for construction of decision and inhibitory trees, rules and tests. Development of extensions of dynamic programming approach for study of trees and rules (counting the number of optimal trees and rules, multi-stage optimization, construction of the set of Pareto optimal points, study of relationships between two cost functions and between cost and uncertainty). Applications to test optimization. Experimental study of trees and systems of rules as algorithms, as classifiers, and as ways for knowledge representation.​​ Details This is main project of the

Average Time Complexity of Decision Trees - Book preparation

Preparation of the book I. Chikalov, Average Time Complexity of Decision Trees, Series Intelligent Systems Reference Library, Vol. 21, 104 p., Springer, 2011​ Details This one year book preparation​ project is based on the results of Igor Chikalov considered in his PhD Thesis and new results obtained at KAUST. Publications See more about this book: Average Time Complexity of Decision Trees I.Chikalov, Average Time Complexity of Decision Trees, Series Intelligent Systems Reference Library, Vol. 21, Springer, 2011 https://www.springer.com/gp/book/9783642226601# Decision tree is a widely used

Combinatorial Machine Learning: A Rough Set Approach - Book preparation

Preparation of the book M. Moshkov, B. Zielosko, Combinatorial Machine Learning: A Rough Set Approach, Series Studies in Computational Intelligence, Vol. 360, 178 p., Springer, 2011 Details The book is used in KAUST as a textbook for the original course CS 361 Combinatorial Machine Learning. It was a one year project financially supported by KAUST. Publications See more about this book: Combinatorial Machine Learning: A Rough Set Approach M.Moshkov, B.Zielosko,​ Combinatorial Machine Learning: A Rough Set Approach, Series Studies in Computational Intelligence, Vol. 360, Springer, 2011 http:/

Three Approaches to Data Analysis, 2011–2012

Initiative Project ​ Details This is one and half year project of three research groups in KAUST, Warsaw University and Warwick University financially supported by KAUST. The aim of project is the familiarization of research community with three theories in data analysis that were developed almost independently but have many common points. This project includes: Preparation of the book I. Chikalov, V. Lozin, I. Lozina, M. Moshkov, H.S. Nguyen, A. Skowron, B. Zielosko, Three Approaches to Data Analysis: Test Theory, Rough Sets and Logical Analysis of Data, Series Intelligent Systems Reference