Support Vector Machines and Evolutionary Algorithms for Classification: Single or Together?

When discussing classification, support vector machines are known to be a capable and efficient technique to learn and predict with high accuracy within a quick time frame. Yet, their black box means to do so make the practical users quite circumspect about relying on it, without much understanding of the how and why of its predictions. The question raised in this book is how can this ‘masked hero’ be made more comprehensible and friendly to the public: provide a surrogate model for its hidden optimization engine, replace the method completely or appoint a more friendly approach to tag along and offer the much desired explanations? Evolutionary algorithms can do all these and this book presents such possibilities of achieving high accuracy, comprehensibility, reasonable runtime as well as unconstrained performance.
Springer

An aparitie	2016
Autor	Catalin Stoean, Ruxandra Stoean
Dimensiuni	15.5 x 0.8 x 23.5 cm
Editura	Springer
Format	Hardback
ISBN	9783319382432
Limba	Engleza
Nr pag	140