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Machines capable of automatic pattern recognition have many fascinating uses in science & engineering as well as in our daily lives. Algorithms for supervised classification, where one infers a decision boundary from a set of training examples, are at the core of this capability. This book takes a close view of data complexity & its role in shaping the theories & techniques in different disciplines & asks: What is missing from current classification techniques? When the automatic classifiers are not perfect, is it a deficiency of the algorithms by design, or is it a difficulty intrinsic to the classification task? How do we know whether we have exploited to the fullest extent the knowledge embedded in the training data? Uunique in its comprehensive coverage & multidisciplinary approach from various methodological & practical perspectives, researchers & practitioners will find this book an insightful reference to learn about current available techniques as well as application areas.
| Serija: | Advanced Information and Knowledge Processing |
| Leidėjas: | Springer London |
| Išleidimo metai: | 2010 |
| Knygos puslapių skaičius: | 316 |
| ISBN-10: | 1849965579 |
| ISBN-13: | 9781849965576 |
| Formatas: | 235 x 155 x 18 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Data Complexity in Pattern Recognition“
