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The feature subset selection reduces the cost of collecting redundant features. It is the main goal of feature subset selection that generating a feature subset which can preserve the most useful information of the original features. The feature selection methods often need expensive cost to find the optimal feature subset. The asynchronous discrete particle swarm optimal search algorithm is proposed...
Given a large number of basis functions that can be potentially more than the number of samples, we consider the problem of learning a sparse target function that can be expressed as a linear combination of a small number of these basis functions. We are interested in two closely related themes: · feature selection, or identifying the basis functions with nonzero coefficients; · estimation accuracy,...
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