Xiao Bai; Edwin R. Hancock; Tin Kam Ho; Richard C. Wilson; Battista Biggio; Antonio Robles-Kelly Springer International Publishing AG (2018) Saatavuus: Tilaustuote Pehmeäkantinen kirja
Springer Sivumäärä: 300 sivua Asu: Pehmeäkantinen kirja Julkaisuvuosi: 2010, 22.10.2010 (lisätietoa) Kieli: Englanti
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.
