A statistical approach to neural networks for pattern recognition

A Statistical Approach to Neural Networks for Pattern Recognition presents a statistical treatment of the Multilayer Perceptron (MLP), which is the most widely used of the neural network models. This book aims to answer questions that arise when statisticians are first confronted with this type of m...

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Xehetasun bibliografikoak
Egile nagusia: Dunne, Robert A.
Formatua: Liburua
Hizkuntza:Undetermined
Argitaratua: Hoboken, N.J. Wiley 2007
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Thư viện lưu trữ: Trung tâm Học liệu Trường Đại học Cần Thơ
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100 |a Dunne, Robert A. 
245 2 |a A statistical approach to neural networks for pattern recognition 
245 0 |c Robert A. Dunne 
260 |a Hoboken, N.J. 
260 |b Wiley 
260 |c 2007 
520 |a A Statistical Approach to Neural Networks for Pattern Recognition presents a statistical treatment of the Multilayer Perceptron (MLP), which is the most widely used of the neural network models. This book aims to answer questions that arise when statisticians are first confronted with this type of model. Throughout the book, the MLP model is extended in several directions to show that a statistical modeling approach can make valuable contributions, and further exploration for fitting MLP models is made possible via the R and S-PLUS® codes that are available on the book's related Web site. A Statistical Approach to Neural Networks for Pattern Recognition successfully connects logistic regression and linear discriminant analysis, thus making it a critical reference and self-study guide for students and professionals alike in the fields of mathematics, statistics, computer science, and electrical engineering. 
650 |a Mạng thần kinh (Khoa học máy tính),Perceptrons,Neural networks (Computer science),Mạng thần kinh nhân tạo 
904 |i Trọng Hiếu 
980 |a Trung tâm Học liệu Trường Đại học Cần Thơ