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Pattern Recognition and Machine Learning for Self-Study I

Kenichiro Ishii, Naonori Ueda, Eisaku Maeda, Hiroshi Murase
Springer Singapore
74.89 € · Hardcover

Bayes decision rule minimum squared error learning support vector machine kernel function convolutional neural network potential function subspace method primal and dual representations of perceptrons generalized linear discriminant function deep learning nearest neighbor rule Phi function decision boundary parametric and nonparametric learning margin

This book explains the basic principles of pattern recognition (PR) and machine learning (ML) in an easy-to-understand manner for beginners who are trying to learn these principles on their own. Readers with a basic knowledge of linear algebra and probability theory will find it easy to follow. Many...

Pattern Recognition and Machine Learning for Self-Study I

Kenichiro Ishii, Naonori Ueda, Eisaku Maeda, Hiroshi Murase
Springer Singapore
74.89 € · eBook

Bayes decision rule minimum squared error learning support vector machine kernel function convolutional neural network potential function subspace method primal and dual representations of perceptrons generalized linear discriminant function deep learning nearest neighbor rule Phi function decision boundary parametric and nonparametric learning margin

This book explains the basic principles of pattern recognition (PR) and machine learning (ML) in an easy-to-understand manner for beginners who are trying to learn these principles on their own. Readers with a basic knowledge of linear algebra and probability theory will find it easy to follow. Many...

Optimization Methods Applied to Power Systems

MDPI
€ · Paperback

Cable joint internal defect thermal probability density power system optimization optimal power flow developed grew wolf optimizer energy internet prosumer energy management consensus demand response day-ahead load forecasting modular predictor feature selection micro-phasor measurement unit

This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programmin...

Optimization Methods Applied to Power Systems

MDPI
€ · Paperback

Cable joint internal defect thermal probability density power system optimization optimal power flow developed grew wolf optimizer energy internet prosumer energy management consensus demand response day-ahead load forecasting modular predictor feature selection micro-phasor measurement unit

This book presents an interesting sample of the latest advances in optimization techniques applied to electrical power engineering. It covers a variety of topics from various fields, ranging from classical optimization such as Linear and Nonlinear Programming and Integer and Mixed-Integer Programmin...

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