Search Results for author: Besim Bilalli

Found 2 papers, 1 papers with code

A data-science pipeline to enable the Interpretability of Many-Objective Feature Selection

1 code implementation30 Nov 2023 Uchechukwu F. Njoku, Alberto Abelló, Besim Bilalli, Gianluca Bontempi

The methodology supports the data scientist in the selection of an optimal feature subset by providing her with high-level information at three different levels: objectives, solutions, and individual features.

Fairness feature selection

PRESISTANT: Learning based assistant for data pre-processing

no code implementations2 Mar 2018 Besim Bilalli, Alberto Abelló, Tomàs Aluja-Banet, Robert Wrembel

Data pre-processing is one of the most time consuming and relevant steps in a data analysis process (e. g., classification task).

General Classification

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