Computational Methods for Data Analysis /

Computational Methods for Data Analysis / / Carlo Cattani, Yeliz Karaca.

This graduate text covers a variety of mathematical and statistical tools for the analysis of big data coming from biology, medicine and economics. Neural networks, Markov chains, tools from statistical physics and wavelet analysis are used to develop efficient computational algorithms, which are th...

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Bibliographic Details
Superior document:Title is part of eBook package: De Gruyter DG Plus eBook-Package 2019
VerfasserIn:
Karaca, Yeliz,
Cattani, Carlo,
Place / Publishing House:Berlin ;, Boston : : De Gruyter, , [2018]
©2019
Year of Publication:2018
Language:English
Series:De Gruyter Textbook
Online Access:
Physical Description:1 online resource (XII, 383 p.)
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Table of Contents:
  • Frontmatter
  • Preface
  • Acknowledgment
  • Contents
  • 1. Introduction
  • 2. Dataset
  • 3. Data preprocessing and model evaluation
  • 4. Algorithms
  • 5. Linear model and multilinear model
  • 6. Decision Tree
  • 7. Naive Bayesian classifier
  • 8. Support vector machines algorithms
  • 9. k-Nearest neighbor algorithm
  • 10. Artificial neural networks algorithm
  • 11. Fractal and multifractal methods with ANN
  • Index

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