Similarity-Based Clustering Recent Developments and Biomedical Applications /

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 ch...

Full description

Bibliographic Details
Call Number:Libro Electrónico
Corporate Author: SpringerLink (Online service)
Other Authors: Villmann, Thomas (Editor), Biehl, M. (Editor), Hammer, Barbara (Editor), Verleysen, Michel (Editor)
Format: Electronic eBook
Language:Inglés
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2009.
Edition:1st ed. 2009.
Series:Lecture Notes in Artificial Intelligence, 5400
Subjects:
Life sciences.
Bioinformatics.
Medicine-Research.
Biology-Research.
Data mining.
Information storage and retrieval systems.
Image processing-Digital techniques.
Computer vision.
Life Sciences.
Computational and Systems Biology.
Biomedical Research.
Data Mining and Knowledge Discovery.
Information Storage and Retrieval.
Computer Imaging, Vision, Pattern Recognition and Graphics.
Online Access:Texto Completo
Table of 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.

Similar Items