A topological classifier to characterize brain states: When shape matters more than variance
Aina Ferrà,
Gloria Cecchini,
Fritz-Pere Nobbe Fisas
et al.
Abstract:Despite the remarkable accuracies attained by machine learning classifiers to separate complex datasets in a supervised fashion, most of their operation falls short to provide an informed intuition about the structure of data, and, what is more important, about the phenomena being characterized by the given datasets. By contrast, topological data analysis (TDA) is devoted to study the shape of data clouds by means of persistence descriptors and provides a quantitative characterization of specific topological f… Show more
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