Get Free Shipping on orders over $0
Combinatorial Machine Learning : A Rough Set Approach - Mikhail Moshkov

Combinatorial Machine Learning

A Rough Set Approach

By: Mikhail Moshkov, Beata Zielosko

Hardcover | 29 June 2011

At a Glance

Hardcover


$185.99

or 4 interest-free payments of $46.50 with

 or 

Ships in 5 to 7 business days

Decision trees and decision rule systems are widely used in different applications

as algorithms for problem solving, as predictors, and as a way for

knowledge representation. Reducts play key role in the problem of attribute

(feature) selection. The aims of this book are (i) the consideration of the sets

of decision trees, rules and reducts; (ii) study of relationships among these

objects; (iii) design of algorithms for construction of trees, rules and reducts;

and (iv) obtaining bounds on their complexity. Applications for supervised

machine learning, discrete optimization, analysis of acyclic programs, fault

diagnosis, and pattern recognition are considered also. This is a mixture of

research monograph and lecture notes. It contains many unpublished results.

However, proofs are carefully selected to be understandable for students.

The results considered in this book can be useful for researchers in machine

learning, data mining and knowledge discovery, especially for those who are

working in rough set theory, test theory and logical analysis of data. The book

can be used in the creation of courses for graduate students.

More in Artificial Intelligence

Agentic AI For Dummies : For Dummies (Computer/Tech) - Pam Baker
Decoding Despair : How AI is Reshaping Psychiatry - Mariam Khayretdinova

RRP $52.95

$44.75

15%
OFF
AI for Business : A Guide to AI Adoption - Jon Whittle

RRP $49.99

$40.75

18%
OFF
The Singularity is Nearer : When We Merge with AI - Ray Kurzweil

RRP $26.99

$22.99

15%
OFF
The Shortest History of AI - Toby Walsh

RRP $27.99

$22.75

19%
OFF
AI Engineering : Building Applications with Foundation Models - Chip Huyen