Overview
- Includes a discussion of descriptive analytic modeling
- Covers visualization in the context of data mining
- Demonstrates modeling with R and other open source software products
- Includes supplementary material: sn.pub/extras
Part of the book series: Computational Risk Management (Comp. Risk Mgmt)
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Table of contents (8 chapters)
Keywords
About this book
Using business-related data to demonstrate models, this descriptive book explains how methods work with some citations, but without detailed references. The data sets and software selected are widely available and can easily be accessed.
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Descriptive Data Mining
Authors: David L. Olson
Series Title: Computational Risk Management
DOI: https://doi.org/10.1007/978-981-10-3340-7
Publisher: Springer Singapore
eBook Packages: Business and Management, Business and Management (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2017
Softcover ISBN: 978-981-10-9847-5Published: 05 July 2018
eBook ISBN: 978-981-10-3340-7Published: 09 December 2016
Series ISSN: 2191-1436
Series E-ISSN: 2191-1444
Edition Number: 1
Number of Pages: XI, 116
Number of Illustrations: 3 b/w illustrations, 60 illustrations in colour
Topics: Big Data/Analytics, Data Mining and Knowledge Discovery, Risk Management