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Practical Neural Network Recipies in C++
book

Practical Neural Network Recipies in C++

by Masters
June 2014
Intermediate to advanced content levelIntermediate to advanced
493 pages
20h 30m
English
Morgan Kaufmann
Content preview from Practical Neural Network Recipies in C++
xii Contents
Other Optimization Criteria 218
Bayesian Confidence Measures 219
Autoassociative Versions 220
When to Use a Probabilistic Neural Network 221
13.
Functional Link Networks 223
Application to Nonlinear Approximation 226
Mathematics of the Functional Link Network 227
When to Use a Functional Link Network 229
14.
Hybrid Networks 231
Functional Link Net as a Hidden Layer 232
Fast Bayesian Confidences 235
Training 238
Attention-based Processing 239
Factorable Problems 242
Training the Data Reduction Networks 243
Splitting Is Not Always Effective 244
15.
Designing the Training Set 245
Number of Samples 246
Communal Random Errors 247
Overfittin ...
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Publisher Resources

ISBN: 9780080514338