000 04190nam a22006255i 4500
001 978-3-642-01805-3
003 DE-He213
005 20160624102129.0
007 cr nn 008mamaa
008 100301s2009 gw | s |||| 0|eng d
020 _a9783642018053
_9978-3-642-01805-3
024 7 _a10.1007/978-3-642-01805-3
_2doi
050 4 _aQH324.2-324.25
072 7 _aPSA
_2bicssc
072 7 _aUB
_2bicssc
072 7 _aCOM014000
_2bisacsh
082 0 4 _a570.285
_223
245 1 0 _aSimilarity-Based Clustering
_h[electronic resource] :
_bRecent Developments and Biomedical Applications /
_cedited by Michael Biehl, Barbara Hammer, Michel Verleysen, Thomas Villmann.
260 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2009.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2009.
300 _aXI, 203 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v5400
505 0 _aI: 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.
520 _aThis 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.
650 0 _aComputer science.
650 0 _aMedicine.
650 0 _aData mining.
650 0 _aInformation storage and retrieval systems.
650 0 _aArtificial intelligence.
650 0 _aComputer vision.
650 0 _aBioinformatics.
650 1 4 _aComputer Science.
650 2 4 _aComputational Biology/Bioinformatics.
650 2 4 _aBiomedicine general.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aBiehl, Michael.
_eeditor.
700 1 _aHammer, Barbara.
_eeditor.
700 1 _aVerleysen, Michel.
_eeditor.
700 1 _aVillmann, Thomas.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642018046
786 _dSpringer
830 0 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v5400
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-01805-3
942 _2EBK8492
_cEBK
999 _c37786
_d37786