Similarity-Based Clustering : Recent Developments and Biomedical Applications / edited by Thomas Villmann, M. Biehl, Barbara Hammer, Michel Verleysen.

Format:

Book

Contributor:

Villmann, Thomas, editor.

Biehl, M., editor.

Hammer, Barbara, 1970- editor.

Verleysen, Michel, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Lecture notes in computer science. Lecture notes in artificial intelligence ; 5400.

Lecture Notes in Artificial Intelligence ; 5400

Language:

English

Subjects (All):

Life sciences.

Bioinformatics.

Medicine.

Data mining.

Information storage and retrieval.

Optical data processing.

Life Sciences, general.

Computational Biology/Bioinformatics.

Biomedicine, general.

Data Mining and Knowledge Discovery.

Information Storage and Retrieval.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Local Subjects:

Life Sciences, general.

Computational Biology/Bioinformatics.

Biomedicine, general.

Data Mining and Knowledge Discovery.

Information Storage and Retrieval.

Computer Imaging, Vision, Pattern Recognition and Graphics.

Physical Description:

1 online resource (XI, 203 pages).

Edition:

First edition 2009.

Contained In:

Springer eBooks

Place of Publication:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2009.

System Details:

text file PDF

Summary:

This book is the outcome of the Dagstuhl Seminar on "Similarity-Based Clustering" held at Dagstuhl Castle, Germany, in Spring 2007. In three chapters, the three fundamental aspects of a theoretical background, the representation of data and their connection to algorithms, and particular challenging applications are considered. Topics discussed concern a theoretical investigation and foundation of prototype based learning algorithms, the development and extension of models to directions such as general data structures and the application for the domain of medicine and biology. Similarity based methods find widespread applications in diverse application domains, including biomedical problems, but also in remote sensing, geoscience or other technical domains. The presentations give a good overview about important research results in similarity-based learning, whereby the character of overview articles with references to correlated research articles makes the contributions particularly suited for a first reading concerning these topics.

Contents:

I: Dynamics of Similarity-Based Clustering

Statistical Mechanics of On-line Learning

Some Theoretical Aspects of the Neural Gas Vector Quantizer

Immediate Reward Reinforcement Learning for Clustering and Topology Preserving Mappings

II: Information Representation

Advances in Feature Selection with Mutual Information

Unleashing Pearson Correlation for Faithful Analysis of Biomedical Data

Median Topographic Maps for Biomedical Data Sets

Visualization of Structured Data via Generative Probabilistic Modeling

III: Particular Challenges in Applications

Learning Highly Structured Manifolds: Harnessing the Power of SOMs

Estimation of Boar Sperm Status Using Intracellular Density Distribution in Grey Level Images

HIV-1 Drug Resistance Prediction and Therapy Optimization: A Case Study for the Application of Classification and Clustering Methods.

Other Format:

Printed edition:

ISBN:

978-3-642-01805-3

9783642018053

Access Restriction:

Restricted for use by site license.