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Business analytics using R - A practical approach [electronic resource]

Material type

E-Book(소장)

Personal Author

Hodeghatta, Umesh R. Nayak, Umesh.

Title Statement

Business analytics using R - A practical approach [electronic resource] / Umesh R. Hodeghatta, Umesh Nayak.

Publication, Distribution, etc

Cham : Springer, c2017.
Berkeley, CA : Apress, c2017.

Physical Medium

1 online resource (xvii, 280 p.) : ill.

ISBN

9781484225134 9781484225141 (e-book)

요약

Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics. This book will discuss and explore the following through examples and case studies: An introduction to R: data management and R functions The architecture, framework, and life cycle of a business analytics project Descriptive analytics using R: descriptive statistics and data cleaning Data mining: classification, association rules, and clustering Predictive analytics: simple regression, multiple regression, and logistic regression This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book. You will: Write R programs to handle data Build analytical models and draw useful inferences from them Discover the basic concepts of data mining and machine learning Carry out predictive modeling Define a business issue as an analytical problem.

General Note

Title from e-Book title page.

Bibliography, Etc. Note

Includes bibliographical references and index.

이용가능한 다른형태자료

Issued also as a book.

Subject Added Entry-Topical Term

Business --Data processing. Management information systems. R (Computer program language).

Short cut

URL

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020		▼a 9781484225134
020		▼a 9781484225141 (e-book)
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084		▼a 658.40380285 ▼2 DDCK
090		▼a 658.40380285
100	1	▼a Hodeghatta, Umesh R.
245	1 0	▼a Business analytics using R - A practical approach ▼h [electronic resource] / ▼c Umesh R. Hodeghatta, Umesh Nayak.
260		▼a Cham : ▼b Springer, ▼c c2017.
260		▼a Berkeley, CA : ▼b Apress, ▼c c2017.
300		▼a 1 online resource (xvii, 280 p.) : ▼b ill.
500		▼a Title from e-Book title page.
504		▼a Includes bibliographical references and index.
520		▼a Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics. This book will discuss and explore the following through examples and case studies: An introduction to R: data management and R functions The architecture, framework, and life cycle of a business analytics project Descriptive analytics using R: descriptive statistics and data cleaning Data mining: classification, association rules, and clustering Predictive analytics: simple regression, multiple regression, and logistic regression This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book. You will: Write R programs to handle data Build analytical models and draw useful inferences from them Discover the basic concepts of data mining and machine learning Carry out predictive modeling Define a business issue as an analytical problem.
530		▼a Issued also as a book.
538		▼a Mode of access: World Wide Web.
650	0	▼a Business ▼x Data processing.
650	0	▼a Management information systems.
650	0	▼a R (Computer program language).
700	1	▼a Nayak, Umesh.
856	4 0	▼u https://oca.korea.ac.kr/link.n2s?url=https://doi.org/10.1007/978-1-4842-2514-1
945		▼a KLPA
991		▼a E-Book(소장)

Holdings Information

Main Library

No.	Location	Call Number	Accession No.	Availability	Due Date	Make a Reservation	Service
No. 1	Location Main Library/e-Book Collection/	Call Number CR 658.40380285	Accession No. E14018781	Availability Loan can not(reference room)	Due Date	Make a Reservation	Service M

Business analytics using R - A practical approach [electronic resource]

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