Abstract
A methodology for IFC has been introduced. This method allows automated derivation of membership functions from data. The idea is to translate sampled probabilities into fuzzy restrictions. Thus, a conceptual switch from the probabilistic to the possibilistic view is applied in order to reason about the data in terms of fuzzy logic. Business applications of MFI have been proposed in the area of marketing analytics in the fields of customer and product analytics, fuzzy target groups, and integrated analytics for individual marketing. A prototype inductive fuzzy classification language (IFCL) has been implemented and applied in experiments with 60 datasets with categorical and numerical target variables in order to evaluate performance improvements by application of the proposed methodology. Seven questions (Sect. 1.1) have guided the research conducted for this thesis. The following list summarizes the answers that this thesis proposes:
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Kaufmann, M. (2014). Precisiating Fuzziness by Induction. In: Inductive Fuzzy Classification in Marketing Analytics. Fuzzy Management Methods. Springer, Cham. https://doi.org/10.1007/978-3-319-05861-0_5
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DOI: https://doi.org/10.1007/978-3-319-05861-0_5
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