Hi Keith, unfortunately KennardStone uses only the unweighted euclidean distance. We will add it on our ToDo, but since there is a hell of work waiting, we can't promise that it is already in the next release...
Hi again, I nearly forgot to mention, that you could use the AttributeWeightsApplier to transform the numeric values of your attributes according to the attribute weights. This will enable you to use KennardStone with weighted distance calculation.
Thanks for that suggestion. It is possible to use AttributeWeightsApplier inside EvolutionaryWeighting? I tried setting up a process inside EvolutionaryWeighting that applies the weights to the data, then runs Kennard Stone. However, I'm getting an error saying that AttributeWeightsApplier doesn't have any attribute weights as an input. Is there some trick to getting that to work?
Hi Keith, it's unnecessary to apply the weights within the evolutionaryWeighting, because the exampleset delievered to the inner operators is already weighted by the current weights.
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Answers
unfortunately KennardStone uses only the unweighted euclidean distance. We will add it on our ToDo, but since there is a hell of work waiting, we can't promise that it is already in the next release...
Greetings,
Sebastian
I nearly forgot to mention, that you could use the AttributeWeightsApplier to transform the numeric values of your attributes according to the attribute weights. This will enable you to use KennardStone with weighted distance calculation.
Greetings,
Sebastian
Thanks,
Keith
it's unnecessary to apply the weights within the evolutionaryWeighting, because the exampleset delievered to the inner operators is already weighted by the current weights.
Greetings,
Sebastian