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An introduction to data analysis using aggregation functions in R[electronic resource] /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	519.50285
書名/作者:	An introduction to data analysis using aggregation functions in R/ by Simon James.
作者:	James, Simon.
出版者:	Cham : : Springer International Publishing :, 2016.
面頁冊數:	x, 199 p. : : ill. (some col.), digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Mathematical statistics - Data processing.
標題:	R (Computer program language)
標題:	Computer Science.
標題:	Computing Methodologies.
標題:	Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
標題:	Applications of Mathematics.
標題:	Mathematics of Computing.
ISBN:	9783319467627
ISBN:	9783319467610
內容註:	Aggregating data with averaging functions -- Transforming data -- Weighted averaging -- Averaging with interaction -- Fitting aggregation functions to empirical data -- Solutions.
摘要、提要註:	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.
電子資源:	http://dx.doi.org/10.1007/978-3-319-46762-7

An introduction to data analysis using aggregation functions in R[electronic resource] /
James, Simon.

An introduction to data analysis using aggregation functions in R[electronic resource] /by Simon James. - Cham :Springer International Publishing :2016. - x, 199 p. :ill. (some col.), digital ;24 cm.

Aggregating data with averaging functions -- Transforming data -- Weighted averaging -- Averaging with interaction -- Fitting aggregation functions to empirical data -- Solutions.

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.

ISBN: 9783319467627

Standard No.: 10.1007/978-3-319-46762-7doiSubjects--Topical Terms:

465468
Mathematical statistics
--Data processing.

LC Class. No.: QA276.45.R3

Dewey Class. No.: 519.50285

An introduction to data analysis using aggregation functions in R[electronic resource] /
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