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Since it looks like your search space is binary strings, you can take advantage of BitXor which is popular in GAs for toggling genes: doMutation[string_, geneMutateProb_] := BitXor[string, RandomVariate[BernoulliDistribution[geneMutateProb], Length[string]]]


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I've spotted three issues with your approach and posted code: Spectral clustering uses the eigenvectors associated with the $k$ smallest eigenvalues of the Laplacian, but your code is selecting those associated with the $k$ largest eigenvalues. You need to Transpose your Kvecs prior to passing them to ClusteringComponents. As currently written, you're ...


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You are missing commas in your last line. Use Print["Der gewichtete Mittelwert ist: ", mWeightedErrorMeanValue , " \ und der Fehler dazu ist: ", mErrorOfWeightedMean] With a=3 and b=5 in the roles of your mWeightedErrorMeanValue and mErrorOfWeightedMean, respectively, compare Print["xyz :" a " abc :" b] 15 abc : xyz : versus Print["xyz :" ...



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