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estimate_sparsity #116

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Yawgmoth90 opened this issue May 30, 2017 · 1 comment
Open

estimate_sparsity #116

Yawgmoth90 opened this issue May 30, 2017 · 1 comment

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@Yawgmoth90
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The function estimate_sparsity currently computes the fitness by changing each component of the decision vector x by the same amount (default 1e-8). This causes issues for problems that are not scaled in a proper way.

A possible fix would be to pass instead the lower and upper bounds of x as arguments, in addition to a number N: the function could compute a random x within the bounds, then for every component of x change it N times (one by one) within the respective bounds, and check if the fitness components are constant in all of the N points obtained.

@darioizzo
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Indeed the current implementation fails miserably on unscaled problems. The proposed solution would definitely fix this. When #110 and #115 are merged a PR would be welcomed.

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