Cantitate/Preț
Produs

Entropy Randomization in Machine Learning: Chapman & Hall/CRC Machine Learning & Pattern Recognition

Autor Yuri S. Popkov, Alexey Yu. Popkov, Yuri A. Dubnov
en Limba Engleză Paperback – 8 oct 2024
Entropy Randomization in Machine Learning presents a new approach to machine learning—entropy randomization—to obtain optimal solutions under uncertainty (uncertain data and models of the objects under study). Randomized machine-learning procedures involve models with random parameters and maximum entropy estimates of the probability density functions of the model parameters under balance conditions with measured data. Optimality conditions are derived in the form of nonlinear equations with integral components. A new numerical random search method is developed for solving these equations in a probabilistic sense. Along with the theoretical foundations of randomized machine learning, Entropy Randomization in Machine Learning considers several applications to binary classification, modelling the dynamics of the Earth’s population, predicting seasonal electric load fluctuations of power supply systems, and forecasting the thermokarst lakes area in Western Siberia.
Features
• A systematic presentation of the randomized machine-learning problem: from data processing, through structuring randomized models and algorithmic procedure, to the solution of applications-relevant problems in different fields
• Provides new numerical methods for random global optimization and computation of multidimensional integrals
• A universal algorithm for randomized machine learning
This book will appeal to undergraduates and postgraduates specializing in artificial intelligence and machine learning, researchers and engineers involved in the development of applied machine learning systems, and researchers of forecasting problems in various fields.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (1) 26466 lei  6-8 săpt.
  CRC Press – 8 oct 2024 26466 lei  6-8 săpt.
Hardback (1) 64534 lei  6-8 săpt.
  CRC Press – 9 aug 2022 64534 lei  6-8 săpt.

Din seria Chapman & Hall/CRC Machine Learning & Pattern Recognition

Preț: 26466 lei

Preț vechi: 37672 lei
-30% Nou

Puncte Express: 397

Preț estimativ în valută:
5067 5211$ 4203£

Carte tipărită la comandă

Livrare economică 19 februarie-05 martie

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9781032307749
ISBN-10: 1032307749
Pagini: 392
Ilustrații: 318
Dimensiuni: 156 x 234 mm
Greutate: 0.73 kg
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC
Seria Chapman & Hall/CRC Machine Learning & Pattern Recognition

Locul publicării:Boca Raton, United States

Public țintă

Postgraduate, Professional, and Undergraduate Advanced

Cuprins

Preface
1. General Concept of Machine Learning
2. Data Sources and Models Chapter
3. Dimension Reduction Methods
4. Randomized Parametric Models
5. Entropy-robust Estimation Procedures for Randomized Models and Measurement Noises
6. Entropy-Robust Estimation Methods for Probabilities of Belonging in Machine Learning Procedures
7. Computational Methods od Randomized Machine Learning 
8. Generation Methods for Random Vectors with Given Probability Density Functions over Compact Sets
9. Information Technologies of Randomized Machine Learning
10. Entropy Classification
11. Randomized Machine Learning in Problems of Dynamic Regression and Prediction
Appendix A: Maximum Entropy Estimate (MEE) and Its Asymptotic Efficiency
Appendix B: Approximate Estimation of Structural Characteristics of Linear Dynamic Regression Model (LDR)
Bibliography

Notă biografică

Yuri S. Popkov: Doctor of Engineering, Professor, Academician of Russian Academy of Sciences; Chief Researcher at Federal Research Center “Computer Science and Control,” Russian Academy of Sciences; Chief Researcher at Trapeznikov Institute of Control Sciences, Russian Academy of Sciences; Professor at Lomonosov Moscow State University. Author of more than 250 scientific publications, including 15 monographs. His research interests include stochastic dynamic systems, optimization, machine learning, and macrosystem modeling.
Alexey Yu. Popkov: Candidate of Sciences, Leading Researcher at Federal Research Center “Computer Science and Control,” Russian Academy of Sciences; author of 47 scientific publications. His research interests include software engineering, high-performance computing, data mining, machine learning, and entropy methods.
Yuri A. Dubnov: MSc in Physics, Researcher at Federal Research Center “Computer Science and Control,” Russian Academy of Sciences. Author of more than 18 scientific publications. His research interests include machine learning, forecasting, randomized approaches, and Bayesian estimation.

Descriere

Entropy Randomization in Machine Learning presents a new approach to machine learning - entropy randomization - to obtain optimal solutions under uncertainty (uncertain data and models of the objects under study).