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Analysis of Large and Complex Data [electronic resource] / edited by Adalbert F.X. Wilhelm, Hans A. Kestler.

Contributor(s): Wilhelm, Adalbert F.X [editor.] | Kestler, Hans A [editor.] | SpringerLink (Online service).
Material type: TextTextSeries: Studies in Classification, Data Analysis, and Knowledge Organization: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Description: XXVI, 656 p. 171 illus., 32 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319252261.Subject(s): Mathematical statistics | Data mining | Statistics | Computer science | Statistical methods | Statistics and Computing/Statistics Programs | Data Mining and Knowledge Discovery | Statistics for Life Sciences, Medicine, Health Sciences | Statistics for Business/Economics/Mathematical Finance/Insurance | Probability and Statistics in Computer Science | BiostatisticsAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 519.5 Online resources: Click here to access online
Contents:
Part I Invited Papers -- Part II Big Data -- Part III Clustering -- Part IV Classification -- Part V Regression and other Statistical Techniques -- Part VI Applications -- Part VII Data Analysis in Marketing -- Part VIII Data Analysis in Finance -- Part IX Data Analysis in Medicine and Life Sciences -- Part X Data Analysis in Musicology -- Part XI Data Analysis in Interdisciplinary Domains -- Part XII Data Analysis in Social, Behavioural and Health Care Sciences -- Part XIII Data Analysis in Library Science -- .
In: Springer eBooksSummary: This book offers a snapshot of the state-of-the-art in classification at the interface between statistics, computer science and application fields. The contributions span a broad spectrum, from theoretical developments to practical applications; they all share a strong computational component. The topics addressed are from the following fields: Statistics and Data Analysis; Machine Learning and Knowledge Discovery; Data Analysis in Marketing; Data Analysis in Finance and Economics; Data Analysis in Medicine and the Life Sciences; Data Analysis in the Social, Behavioural, and Health Care Sciences; Data Analysis in Interdisciplinary Domains; Classification and Subject Indexing in Library and Information Science. The book presents selected papers from the Second European Conference on Data Analysis, held at Jacobs University Bremen in July 2014. This conference unites diverse researchers in the pursuit of a common topic, creating truly unique synergies in the process.p>.
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Part I Invited Papers -- Part II Big Data -- Part III Clustering -- Part IV Classification -- Part V Regression and other Statistical Techniques -- Part VI Applications -- Part VII Data Analysis in Marketing -- Part VIII Data Analysis in Finance -- Part IX Data Analysis in Medicine and Life Sciences -- Part X Data Analysis in Musicology -- Part XI Data Analysis in Interdisciplinary Domains -- Part XII Data Analysis in Social, Behavioural and Health Care Sciences -- Part XIII Data Analysis in Library Science -- .

This book offers a snapshot of the state-of-the-art in classification at the interface between statistics, computer science and application fields. The contributions span a broad spectrum, from theoretical developments to practical applications; they all share a strong computational component. The topics addressed are from the following fields: Statistics and Data Analysis; Machine Learning and Knowledge Discovery; Data Analysis in Marketing; Data Analysis in Finance and Economics; Data Analysis in Medicine and the Life Sciences; Data Analysis in the Social, Behavioural, and Health Care Sciences; Data Analysis in Interdisciplinary Domains; Classification and Subject Indexing in Library and Information Science. The book presents selected papers from the Second European Conference on Data Analysis, held at Jacobs University Bremen in July 2014. This conference unites diverse researchers in the pursuit of a common topic, creating truly unique synergies in the process.p>.

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