| Description |
1 online resource (xiv, 247 pages) |
| Bibliography |
Includes bibliographical references and index. |
| Contents |
Machine learning and financial engineering -- Neural networks -- Wavelet neural networks -- Model selection : selecting the architecture of the network -- Variable selection : determining the explanatory variables -- Model adequacy testing : determining the networks future performance -- Modeling the uncertainty: from point estimates to prediction intervals -- Modeling financial temperature derivatives -- Modeling financial wind derivatives -- Predicting chaotic time series -- Classification of breast cancer cases. |
| Summary |
Through extensive examples and case studies, Wavelet Neural Networks provides a step-by-step introduction to modeling, training, and forecasting using wavelet networks. The acclaimed authors present a statistical model identification framework to successfully apply wavelet networks in various applications, specifically, providing the mathematical and statistical framework needed for model selection, variable selection, wavelet network construction, initialization, training, forecasting and prediction, confidence intervals, prediction intervals, and model adequacy testing. |
| Subject |
Wavelets (Mathematics)
|
|
Neural networks (Computer science)
|
|
Financial engineering.
|
|
Neural Networks, Computer |
|
Ondelettes. |
|
Réseaux neuronaux (Informatique) |
|
Ingénierie financière. |
|
Financial engineering |
|
Neural networks (Computer science) |
|
Wavelets (Mathematics) |
| Added Author |
Zapranis, Achilleas, 1965-
|
| Other Form: |
Print version: Alexandridis, Antonis K. Wavelet neural networks. Hoboken, New Jersey : John Wiley & Sons, Inc., [2014] 9781118592526 (DLC) 2013047838 |
| ISBN |
9781118596296 (epub) |
|
1118596293 (epub) |
|
9781118595503 (pdf) |
|
1118595505 (pdf) |
|
9781118596272 |
|
1118596277 |
|
9781306685009 |
|
1306685001 |
|
(cloth) |
|
More Resources