An Introduction to Data Analysis using Aggregation Functions in R (Record no. 56021)
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fixed length control field | 03349nam a22005175i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-319-46762-7 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20200421111849.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 161107s2016 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783319467627 |
-- | 978-3-319-46762-7 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 006 |
100 1# - AUTHOR NAME | |
Author | James, Simon. |
245 13 - TITLE STATEMENT | |
Title | An Introduction to Data Analysis using Aggregation Functions in R |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | X, 199 p. 29 illus., 20 illus. in color. |
505 0# - FORMATTED CONTENTS NOTE | |
Remark 2 | Aggregating data with averaging functions -- Transforming data -- Weighted averaging -- Averaging with interaction -- Fitting aggregation functions to empirical data -- Solutions. |
520 ## - SUMMARY, ETC. | |
Summary, etc | This textbook helps future data analysts comprehend aggregation function theory and methods in an accessible way, focusing on a fundamental understanding of the data and summarization tools. Offering a broad overview of recent trends in aggregation research, it complements any study in statistical or machine learning techniques. Readers will learn how to program key functions in R without obtaining an extensive programming background. Sections of the textbook cover background information and context, aggregating data with averaging functions, power means, and weighted averages including the Borda count. It explains how to transform data using normalization or scaling and standardization, as well as log, polynomial, and rank transforms. The section on averaging with interaction introduces OWS functions and the Choquet integral, simple functions that allow the handling of non-independent inputs. The final chapters examine software analysis with an emphasis on parameter identification rather than technical aspects. This textbook is designed for students studying computer science or business who are interested in tools for summarizing and interpreting data, without requiring a strong mathematical background. It is also suitable for those working on sophisticated data science techniques who seek a better conception of fundamental data aggregation. Solutions to the practice questions are included in the textbook. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
General subdivision | Mathematics. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-319-46762-7 |
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Koha item type | eBooks |
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-- | Springer International Publishing : |
-- | Imprint: Springer, |
-- | 2016. |
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-- | txt |
-- | rdacontent |
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-- | computer |
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-- | rdamedia |
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-- | online resource |
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-- | text file |
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-- | rda |
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-- | Computer science. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Computer science |
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-- | Computers. |
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-- | Applied mathematics. |
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-- | Engineering mathematics. |
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-- | Statistics. |
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-- | Computer Science. |
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-- | Computing Methodologies. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Applications of Mathematics. |
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-- | Mathematics of Computing. |
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-- | ZDB-2-SCS |
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