Proceedings of the Seventh SIAM International Conference on Data Mining: Proceedings of the Seventh SIAM International Conference on Data Mining, Minneapolis, MN, April 26–28, 2007
Gespeichert in:
Bibliographische Detailangaben
Weitere beteiligte Personen: Apté, Chidanand V. (HerausgeberIn), Skillicorn, David B. (HerausgeberIn), Liu, Bing 1963- (HerausgeberIn), Parthasarathy, Srinivasan (HerausgeberIn)
Format: Elektronisch E-Book
Sprache:Englisch
Veröffentlicht: Philadelphia, Pennsylvania Society for Industrial and Applied Mathematics, SIAM [2007]
Schlagwörter:
Links:https://doi.org/10.1137/1.9781611972771
https://doi.org/10.1137/1.9781611972771
https://doi.org/10.1137/1.9781611972771
https://doi.org/10.1137/1.9781611972771
https://epubs.siam.org/doi/book/10.1137/1.9781611972771
https://zbmath.org/?q=an:1203.68002
Abstract:The Seventh SIAM International Conference on Data Mining (SDM 2007) continues a series of conferences whose focus is the theory and application of data mining to complex datasets in science, engineering, biomedicine, and the social sciences. These datasets challenge our abilities to analyze them because they are large and often noisy. Sophisticated, highperformance, and principled analysis techniques and algorithms, based on sound statistical foundations, are required. Visualization is often critically important; tuning for performance is a significant challenge; and the appropriate levels of abstraction to allow end-users to exploit sophisticated techniques and understand clearly both the constraints and interpretation of results are still something of an open question
Beschreibung:Includes bibliographical references and index
Umfang:1 Online-Ressources (xiv, 648 pages) Illustrationen, Diagramme
ISBN:9781611972771