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.
General
Is the information for this product incomplete, wrong or inappropriate?
Let us know about it.
Does this product have an incorrect or missing image?
Send us a new image.
Is this product missing categories?
Add more categories.
Review This Product
No reviews yet - be the first to create one!