Core Data Analysis

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With in-depth descriptions of data analysis techniques both for summarizing and correlation, the author's unconventional approach employs the concept of multivariate data summarization as an alternative to conventional machine-learning prediction methods.

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Title Statements

Full title :Core Data Analysis

Summary

Edition Statements

Publication Date:2019.
Edition:2nd ed

Publication Statements

Publisher(s):Springer International Publishing AG
Place of Publication:Cham
Language:eng
Publication Date:2019.

Notes

3.2 Two-D Linear Regression and Special Cases

The Physical Object

Description:1 online resource (536 pages)

Edition Identifiers

ISBN:9783030002718, 3030002713
oclc:on1122921072
LC Classification:QA75.5-76.95

Intro; Preface to the Second Edition; Preface to the First Edition; Acknowledgements; Contents; 1 Topics in Substance of Data Analysis; Abstract; 1.1 Summarization and Correlation: Main Goals of Core Data Analysis; 1.1.1 The Goals for Knowledge Enhancing; 1.1.2 Other Approaches; 1.1.3 Structure of Data Analysis Problem; 1.1.4 Teaching Paradigm; 1.2 Case Study Problems; 1.2.1 Quantitative Entity-to-Feature Data Tables; 1.2.2 Mixed Scale Entity-to-Feature Data Tables; 1.2.3 Similarity or Network Data; 1.3 An Account of Data Visualization; 1.3.1 General; 1.3.2 Publicizing and Highlighting

1.3.3 Integrating Different Aspects1.3.4 Narrating a Story; 1.4 The Role of Data Analysis; 1.4.1 Current Success of Data Analysis and Data Table; 1.4.2 A Great Success Story: Kepler's Planetary Motion; 1.4.3 Failures of Data Analysis: Counter-Intuitive Cases; 1.4.4 Insubstantial Patterns and Their Causes; 1.5 Knowledge Shaped as Classification; 1.5.1 Classification as Soft Knowledge; 1.5.2 Goals of Classification; 1.5.3 Forms of Classification; 1.6 Summary; References; Articles; 2 Quantitative Summarization; Abstract; 2.1 Encoder-Decoder Data Summarization

2.1.1 Structure of a Summarization Proble…