Machine Learning and Data Mining in Pattern Recognition [electronic resource] : 7th International Conference, MLDM 2011, New York, NY, USA, August 30 – September 3, 2011. Proceedings / edited by Petra Perner.
Material type:
TextSeries: Lecture Notes in Computer Science ; 6871Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Description: XII, 614 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783642231995Subject(s): Computer science | Database management | Data mining | Artificial intelligence | Computer vision | Optical pattern recognition | Computer Science | Artificial Intelligence (incl. Robotics) | Mathematical Logic and Formal Languages | Database Management | Data Mining and Knowledge Discovery | Pattern Recognition | Image Processing and Computer VisionAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 LOC classification: Q334-342TJ210.2-211.495Online resources: Click here to access online
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Springer eBooksSummary: This book constitutes the refereed proceedings of the 7th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2011, held in New York, NY, USA. The 44 revised full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized in topical sections on classification and decision theory, theory of learning, clustering, appilication in medicine, Webmining and information mining; and machine learning and image mining.
E-BOOKS
| Current library | Home library | Call number | Materials specified | URL | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|
| IMSc Library | IMSc Library | Link to resource | Available | EBK9834 |
This book constitutes the refereed proceedings of the 7th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2011, held in New York, NY, USA. The 44 revised full papers presented were carefully reviewed and selected from 170 submissions. The papers are organized in topical sections on classification and decision theory, theory of learning, clustering, appilication in medicine, Webmining and information mining; and machine learning and image mining.
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