When dealing with high dimensional and low sample size data, feature selection is often needed to help reduce the dimension of the variable space while optimizing the classification task. Few tools exist for selecting variables in such data sets, especially when classes are numerous (2). We have...

Two well known stochastic optimization algorithms, simulated annealing and genetic algorithm are compared when using a sample to minimize an objective function which is the expectation of a random variable. Since they lead to minimum depending on the sample, a weighted version of simulated...