Core data analysis : summarization, correlation, and visualization
- 2nd ed.
- Cham : Springer, 2019
- xv, 524 p. : ill. ; 24 cm.
- Undergraduate topics in computer science .
Includes bibliographical references and index.
This text examines the goals of data analysis with respect to enhancing knowledge, and identifies data summarization and correlation analysis as the core issues. Data summarization, both quantitative and categorical, is treated within the encoder-decoder paradigm bringing forward a number of mathematically supported insights into the methods and relations between them. Two Chapters describe methods for categorical summarization: partitioning, divisive clustering and separate cluster finding and another explain the methods for quantitative summarization, Principal Component Analysis and PageRank.
9783030002701
Data mining Mathematical statistics Data processing