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Introduction to algorithms for data mining and machine learning / Xin-She Yang.

By: Material type: TextTextPublisher: London, United Kingdom ; San Diego, CA, United States : Academic Press, an imprint of Elsevier, 2019Description: viii, 173 pages : illustrations ; 26 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780128172179
  • 0128172177
Subject(s): Genre/Form: Additional physical formats: Print version:: Introduction to algorithms for data mining and machine learning.DDC classification:
  • 006.312 23
LOC classification:
  • QA76.9.D343 YAN
Online resources:
Contents:
Introduction to optimization -- Mathematical foundations -- Optimization algorithms -- Data fitting and regression -- Logistic regression, PCA, LDA, and ICA -- Data mining techniques -- Support vector machine and regression -- Neural networks and deep learning.
Summary: Introduction to Algorithms for Data Mining and Machine Learning introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematical approach, well selected examples, and practical software recommendations help readers develop confidence in their data modeling skills so they can process and interpret data for classification, clustering, curve-fitting and predictions. Masterfully balancing theory and practice, it is especially useful for those who need relevant, well explained, but not rigorous (proofs based) background theory and clear guidelines for working with big data.
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Holdings
Item type Current library Collection Call number Copy number Status Barcode
Open Shelf Books Open Shelf Books Main Library -University of Zimbabwe Main Library Stack Room 2 Open Shelf QA76.9.D343 YAN (Browse shelf(Opens below)) 1 Available 36030001582

Includes bibliographical references (pages 163-170) and index.

Introduction to optimization -- Mathematical foundations -- Optimization algorithms -- Data fitting and regression -- Logistic regression, PCA, LDA, and ICA -- Data mining techniques -- Support vector machine and regression -- Neural networks and deep learning.

Introduction to Algorithms for Data Mining and Machine Learning introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematical approach, well selected examples, and practical software recommendations help readers develop confidence in their data modeling skills so they can process and interpret data for classification, clustering, curve-fitting and predictions. Masterfully balancing theory and practice, it is especially useful for those who need relevant, well explained, but not rigorous (proofs based) background theory and clear guidelines for working with big data.

Online resource; title from digital title page (ScienceDirect, viewed July 14, 2020).

Master record variable field(s) change: 050, 650

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