ENGLISH

Computational Methods for Data Analysis

By Yeliz Karaca; Carlo Cattani

Book information

Publisher
de Gruyter
Year
2018
ISBN
9783110496369, 9783110496352
Language
english
Format
PDF
Filesize
3 MB (3310367 bytes)
Pages
395\396
Time added
2023-05-30 13:48:06

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. Introduces mathematical and statistical methods for data analysis, with applications to biology, medicine and economics Combines theory and applications in the processing of real-life data Algorithms and examples using Matlab are included 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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