Scientific data mining : a practical perspective / Chandrika Kamath.
Material type: TextPublication details: Philadelphia : Society for Industrial and Applied Mathematics, c2009.Description: xviii, 286 p. : ill. ; 26 cmISBN:- 9780898716757
- QA76.9.D343 K151 2009
- ST 530
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Open Shelf Books | Al-Ghazali Library | BKS | QA76.9.D343 K151 2009 (Browse shelf(Opens below)) | 1 | Available | GHAZ13042455 |
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QA76.9.D32 H762 2014 SQL Database for beginners/ | QA76.9.D343 D232 2010 Data mining : | QA76.9.D343 .D232 2010 Data mining for business applications / | QA76.9.D343 K151 2009 Scientific data mining : | QA76.9.D343 L438 2008 Learning classifier systems in data mining / | QA76.9.D343 M266 2009 Managing and mining uncertain data / | QA76.9.D343 S416 2010 Scientific data mining and knowledge discovery : |
Includes bibliographical references (p. 235-277) and index.
Data mining in science and engineering -- Common themes in mining scientific data -- The scientific data mining process -- Reducing the size of the data -- Fusing different data modalities -- Enhancing image data -- Finding objects in the data -- Extracting features describing the objects -- Reducing the dimension of the data -- Finding patterns in the data -- Visualizing the data and validating the results -- Scientific data mining systems -- Lessons learned, challenges, and opportunities.
Chandrika Kamath describes how techniques from the multi-disciplinary field of data mining can be used to address the modern problem of data overload in science and engineering domains. Starting with a survey of analysis problems in different applications, it identifies the common themes across these domains.