Ludmila Kuncheva's Home Page

Google Scholar Profile
Fellow of IAPR
Feature article in IAPR's Newsletter, January 2015


Reviewing Revolution!!! - A personal opinion

Project: "Prototype Selection from Streaming, Drifting and Partly Labelled Data Using Classifier Ensembles" sponsored by The Leverhulme Trust (RPG_2015_188).

Research

---

My research has always gravitated towards pattern recognition and classification. I have dabbled in almost all aspects of the classical paradigm: feature selection, classification, clustering, data editing, etc. I have a soft spot for multiple classifier systems (classifier ensembles), specifically ensemble diversity.

Recent topics

Restricted set classification (RSC)        Image Segmentation Feature Selection

---

Books

Combining Pattern Classifiers. Methods and Algorithms, Wiley, second edition, 2014.				Fuzzy Classifier Design, Springer, 2000.
	ISBN: 978-1-118-31523-1 384 pages October 2014 Combination methods		First Edition, 2004 Editorial Reviews IEEE TNN Review Errata

---

MATLAB Libraries

Ensemble diversity (reference Kuncheva and Whitaker, 2003) Combination methods (Kuncheva, 2014) Generating data with concept drift (reference Narasimhamurthy and Kuncheva, 2007) Bayesian analysis for comparing two classifiers Restricted Set Classification (reference Kuncheva, 2010; Kuncheva and Jackson, 2014; Kuncheva et al., 2017)

---

Teaching

---

Pattern Recognition and Neural Networks, 2019.
	Full text ISBN: 9780244232528 Paperback, 230 pages, Price: £40.77 Lecture slides ML 2021/2022 (235Mb)
A First Course in Mathematics for Computing, 2014.		A MATLAB Exercise Book, 2020, Second edition.
	Full text ISBN: 9781291785630 Paperback, 133 Pages, Price: £29.94 Ships in 3–5 business days		Full text ISBN: 9780244253288 Paperback, 182 pages, Price: £42.00
MathWorks promotion site		MATLAB Exercise Book Solutions