Speaker
Description
EI-SCORE is a Python application that builds an explainable and interpretable composite indicator based on "if-then" decision rules induced by Dominance-based Rough Set Approach (DRSA). The software provides an intuitive, user-friendly interface and implements a recently introduced methodology for DRSA-based composite indicator construction. It constructs the indicator from a learning set of labeled reference units and subsequently updates it as new labeled units are provided through an incremental learning process. EI-SCORE fully supports classification and scoring problems, handles missing values in the description of units, and accepts qualitative criteria. Illustrative examples and a user manual demonstrate the software’s applicability. The results include unit-level explanations of classifications or scores, making the tool particularly useful for policy analysis, performance evaluation, and multiple criteria decision support.
| Keywords | Composite indicators; Decision rules; Dominance-based rough set approach; Incremental learning; Multiple criteria decision aiding |
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| Participation in the SNSF Early-Stage Researcher Support and Award Scheme | I am submitting a regular presentation and would like to participate in the SNSF Early-Stage Researcher Support and Award Scheme. |