scikit-weak is a Python library for weakly supervised learning, compatible with (and based on) scikit-learn.
I'm the primary developer and mantainer of the library, which also feature contributions by
Julian Lienen from Paderborn University.
The library is open-source and available on GitHub and
PyPi.
The library currently focuses on learning from imprecise data, self-supervised learning
and label regularization problems, by providing a framework for management and representation of weakly supervised data,
state-of-the-art classification algorithms, as well as pre-processing, data management, and evaluation utilities.
DSS Quality Assessment
DSS Quality Assessment is a Web Tool for the assessment of data-driven decision support systems, especially those based on AI and ML methodologies.
The Web Tool encompassess different functionalities to provide a holistic approach to quality assessment, in particular it allows to:
evaluate the similarity of datasets, evaluate the calibration and robustness of decision support systems, as well as evaluate the utility and impact
of a decision support system on human decision-making. The web tool was developed at the MUDI Lab of the University of Milano-Bicocca and draws from
multiple years of research conducted at the same lab. The web tool is available here.
COVID-19 Blood-ML
The aim of this project was to develop diagnostic and prognostic models for COVID-19 disease, based on
blood test data. The project has led to the collection of multiple datasets from several hospitals and clinics
around 4 countries (Italy, Spain, Brazil, Ethiopia), which are publicly available (for benchmarking, analysis and model
development purposes) on Zenodo:
