AutoMAT: Automated machine learning: Modelling, Auditing and Testings
What We Do
|Tuning of model hyperparameters, features transformation and features selection are activities that can be automated.
Can and should in order to create more time for creative work of data scientists.
Our group develop new algorithms and tools for AutoML (automated model building), AutoEDA (automated exploratory data analysis) and AutoVAT (automated validation, auditing and testing).
,,MLGenSig: Machine Learning Methods for building the Integrated Genetic Signatures''
,,DALEX: Descriptive mAchine Learning EXplanations''
Intsvy: An R package for analyzing international large-scale assessment data
Daniel Caro, Przemysław Biecek (2017)
Journal of Statistical Software https://www.jstatsoft.org/article/view/v081i07
Comprehensive graphical presentation of data from incurred sample reanalysis
Rudzki P, Biecek P, Kaza M (2017)
archivist: An R Package for Managing, Recording and Restoring Data Analysis Results
Marcin Kosiński, Przemysław Biecek (2017)
Journal of Statistical Software https://www.jstatsoft.org/article/view/v082i11
- Kamil Romaszko, Magda Tatarynowicz, Mateusz Urbański, Przemysław Biecek (2019), modelDown: automated website generator with interpretable documentation for predictive machine learning models, Journal of Open Source Software https://www.theoj.org/joss-papers/joss.01444/10.21105.joss.01444.pdf
- Alicja Gosiewska, Przemyslaw Biecek (2019), SAFE ML: Surrogate Assisted Feature Extraction for Model Learning, ARXIV: arXiv:1902.11035v1 https://arxiv.org/abs/1902.11035
Have a Project in Mind?
Please get in touch with the head of the group.