Feature selection is used to improve performance of learning algorithms by finding a minimal subset of relevant features. Since the process of feature selection is computationally ...
Mark Last, Abraham Kandel, Oded Maimon, Eugene Ebe...
In this paper, we consider the problem of selection on coarse-grained distributed memory parallel computers. We discuss several deterministic and randomized algorithms for paralle...
Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contexts including pattern recognition, adaptive cont...
The paper examines various applicability issues of the negative selection algorithms (NSA). Recently, concerns were raised on the use of NSAs, especially those using real-valued r...