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Core Data Analysis: Summarization, Correlation, and Visualization (Undergraduate Topics in Computer Science)

By: Boris Mirkin (Author)

1 in stock

Ksh 12,550.00

Format: Paperback or Softback

ISBN-10: 3030002705

ISBN-13: 9783030002701

Collection / Series: Undergraduate Topics in Computer Science

Collection Type: Publisher collection

Edition statement: Second Edition 2019

Publisher: Springer Nature Switzerland AG

Imprint: Springer Nature Switzerland AG

Country of Manufacture: CH

Country of Publication: GB

Publication Date: Apr 18th, 2019

Publication Status: Active

Product extent: 524 Pages

Weight: 842.00 grams

Dimensions (height x width x thickness): 15.60 x 23.40 x 2.90 cms

Product Classification / Subject(s): Mathematical & statistical software
Algorithms & data structures
Data mining
Computer security
Network security

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  • Description

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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-containedCore 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. 

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. 

Get Core Data Analysis: Summarization, Correlation, and Visualization by at the best price and quality guranteed only at Werezi Africa largest book ecommerce store. The book was published by Springer Nature Switzerland AG and it has pages. Enjoy Shopping Best Offers & Deals on books Online from Werezi - Receive at your doorstep - Fast Delivery - Secure mode of Payment

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