## Book description

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 then used for the processing of real-life data using Matlab.

## Table of contents

- Cover
- Title Page
- Copyright
- 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

## Product information

- Title: Computational Methods for Data Analysis
- Author(s):
- Release date: December 2018
- Publisher(s): De Gruyter
- ISBN: 9783110493603

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