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Anotace knihy

This volume presents a neural network architecture for the prediction of conditional probability densities - which is vital when carrying out universal approximation on variables which are either strongly skewed or multimodal. Two alternative approaches are discussed: the GM network, in which all parameters are adapted in the training scheme, and the GM-RVFL model which draws on the random functional link net approach. Points of particular interest are: - it examines the modification to standard approaches needed for conditional probability prediction; - it provides the first real-world test results for recent theoretical findings about the relationship between generalisation performance of committees and the over-flexibility of their members; This volume will be of interest to all researchers, practitioners and postgraduate / advanced undergraduate students working on applications of neural networks - especially those related to finance and pattern recognition.

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Zařazení knihy Knihy v angličtině Society & social sciences Society & culture: general Social issues & processes

• Plný název: Neural Networks for Conditional Probability Estimation
• Podnázev: Forecasting Beyond Point Predictions
• Autor: Dirk Husmeier
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 275
• EAN: 9781852330958
• ISBN: 1852330953
• ID: 02181954
• Nakladatelství: Springer London Ltd
• Hmotnost: 462 g
• Rozměry: 235 × 155 × 17 mm
• Datum vydání: 22. February 1999

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