Analysis of Large and Complex Data

ISBN-13: 9783319252247 / Angielski / Miękka / 2016 / 656 str.

Adalbert Wilhelm; Hans Kestler

Opis

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.

Recenzje

“Analysis of Large and Complex Data is a useful book for those who are very well read in sophisticated data analysis across variety of disciplines and are looking for a book that captures state-of-the-art scientific papers across a wide cross-section.” (Jonathan P. Wanderer, Anesthesia & Analgesia, Vol. 125 (1), July, 2017)

Spis treści

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.- 

Blurb

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>