Core Data Analysis: Summarization, Correlation, and Visualization (Paperback, 2nd ed. 2019)

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. Features: * An in-depth presentation of K-means partitioning including a corresponding Pythagorean decomposition of the data scatter. * Advice regarding such issues as clustering of categorical and mixed scale data, similarity and network data, interpretation aids, anomalous clusters, the number of clusters, etc. * Thorough attention to data-driven modelling including a number of mathematically stated relations between statistical and geometrical concepts including those between goodness-of-fit criteria for decision trees and data standardization, similarity and consensus clustering, modularity clustering and uniform partitioning. New edition highlights: * Inclusion of ranking issues such as Google PageRank, linear stratification and tied rankings median, consensus clustering, semi-average clustering, one-cluster clustering * Restructured to make the logics more straightforward and sections self-contained Core Data Analysis: Summarization, Correlation and Visualization is aimed at those who are eager to participate in developing the field as well as appealing to novices and practitioners.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Undergraduate Topics in Computer Science
Release date:	April 2019
First published:	2019
Authors:	Boris Mirkin
Dimensions:	235 x 155 x 29mm (L x W x T)
Format:	Paperback
Pages:	524
Edition:	2nd ed. 2019
ISBN-13:	978-3-03-000270-1
Categories:	Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Computing & IT > Computer communications & networking > Network security Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems
LSN:	3-03-000270-5
Barcode:	9783030002701

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