Synopsis
Data alone are worth almost nothing. While data collection is increasing exponentially worldwide, a clear distinction between retrieving data and obtaining knowledge has to be made. Data are retrieved while measuring phenomena or gathering facts. Knowledge refers to data patterns and trends that are useful for decision making. Data interpretation creates a challenge that is particularly present in system identification, where thousands of models may explain a given set of measurements. Manually interpreting such data is not reliable. One solution is to use data mining. This book thus proposes an integration of techniques from data mining, a field of research where the aim is to find knowledge from data, into an existing multiple-model system identification methodology. In addition to providing information about the candidate model space, data mining is found to be a valuable tool for supporting decisions related to subsequent sensor placement.
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About the Author
Sandro was born in Switzerland in 1981. He has a Master degree in computer science and a PhD in data mining from the Ecole Polytechnique Fédérale de Lausanne (EPFL). His interests include data mining, data analysis, statistics, decision support, behavioral targeting and search engine optimization (SEO). He is also blogger at www.dataminingblog.com
"About this title" may belong to another edition of this title.
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Data Mining
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VDM Verlag Dr. Müller, 2009
ISBN 10: 3639207564
ISBN 13: 9783639207569
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Taschenbuch. Condition: Neu. Data Mining | Applications in Civil Engineering | Sandro Saitta | Taschenbuch | Englisch | VDM Verlag Dr. Müller | EAN 9783639207569 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 101455247
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Data alone are worth almost nothing. While data collection is increasing exponentially worldwide, a clear distinction between retrieving data and obtaining knowledge has to be made. Data are retrieved while measuring phenomena or gathering facts. Knowledge refers to data patterns and trends that are useful for decision making. Data interpretation creates a challenge that is particularly present in system identification, where thousands of models may explain a given set of measurements. Manually interpreting such data is not reliable. One solution is to use data mining. This book thus proposes an integration of techniques from data mining, a field of research where the aim is to find knowledge from data, into an existing multiple-model system identification methodology. In addition to providing information about the candidate model space, data mining is found to be a valuable tool for supporting decisions related to subsequent sensor placement. Seller Inventory # 9783639207569