Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi‐layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.
Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi‐layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.
Minimum Error Entropy Classification
262
Minimum Error Entropy Classification
262Paperback(2013)
Product Details
| ISBN-13: | 9783642437427 |
|---|---|
| Publisher: | Springer Berlin Heidelberg |
| Publication date: | 08/09/2014 |
| Series: | Studies in Computational Intelligence , #420 |
| Edition description: | 2013 |
| Pages: | 262 |
| Product dimensions: | 6.10(w) x 9.25(h) x 0.02(d) |