Core Data Analysis: Summarization, Correlation, and Visualization

Nonfiction, Computers, Advanced Computing, Programming, Data Modeling & Design, Networking & Communications, Computer Security, General Computing
Cover of the book Core Data Analysis: Summarization, Correlation, and Visualization by Boris Mirkin, Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Boris Mirkin ISBN: 9783030002718
Publisher: Springer International Publishing Publication: April 15, 2019
Imprint: Springer Language: English
Author: Boris Mirkin
ISBN: 9783030002718
Publisher: Springer International Publishing
Publication: April 15, 2019
Imprint: Springer
Language: English

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. 

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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. 

More books from Springer International Publishing

Cover of the book Case Studies in Medical Toxicology by Boris Mirkin
Cover of the book Quantum Plasmonics by Boris Mirkin
Cover of the book Periconception in Physiology and Medicine by Boris Mirkin
Cover of the book Towards Global Sustainability by Boris Mirkin
Cover of the book A Mathematical Prelude to the Philosophy of Mathematics by Boris Mirkin
Cover of the book Network Coding at Different Layers in Wireless Networks by Boris Mirkin
Cover of the book Knowledge, Morals and Practice in Kant’s Anthropology by Boris Mirkin
Cover of the book Iatrogenic Effects of Orthodontic Treatment by Boris Mirkin
Cover of the book English for Writing Research Papers by Boris Mirkin
Cover of the book Tocqueville and Beaumont by Boris Mirkin
Cover of the book The Legacy of Courtly Literature by Boris Mirkin
Cover of the book China Ethnic Statistical Yearbook 2016 by Boris Mirkin
Cover of the book International Research on Education for Sustainable Development in Early Childhood by Boris Mirkin
Cover of the book Animal Models of Ophthalmic Diseases by Boris Mirkin
Cover of the book Geometric Invariant Theory for Polarized Curves by Boris Mirkin
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy