Benchmarking reservoir computing on time-independent classification tasks
Luı́s A. Alexandre, Mark J. Embrechts, Jonathan D. Linton · 2009
This paper presents an extensive evaluation of reservoir computing for the case of classification problems that do not depend on time.We discuss how it is possible to adapt the reservoir approach to learning for the case of static classification problems. Then we present a set of experiments against K-PLS, MLP with entropic cost function and LS-SVM showing that this approach is quite competitive and has the advantage of having only one parameter to be chosen.