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Feature construction using explanations of individual predictions
Feature construction can contribute to comprehensibility and performance of machine learning models.
The Digital Synaptic Neural Substrate: A New Approach to Computational Creativity
It uses selected attributes from objects in various domains (e. g. chess problems, classical music, renowned artworks) and recombines them in such a way as to generate new attributes that can then, in principle, be used to create novel objects of creative value to humans relating to any one of the source domains.
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