Evolutionary optimization of machine learning workflows
| Thesis title in Czech: | Optimalizace metod strojového učení na základě evolučních algoritmů |
|---|---|
| Thesis title in English: | Evolutionary optimization of machine learning workflows |
| Key words: | Strojové učení, Evoluční algoritmy, Meta-učení, Workflows |
| English key words: | Machine learning, Evolutionary computing, Meta-learning, Workflows |
| Academic year of topic announcement: | 2018/2019 |
| Thesis type: | Bachelor's thesis |
| Thesis language: | angličtina |
| Department: | Department of Theoretical Computer Science and Mathematical Logic (32-KTIML) |
| Supervisor: | Mgr. Roman Neruda, CSc. |
| Author: | hidden - assigned and confirmed by the Study Dept. |
| Date of registration: | 02.11.2018 |
| Date of assignment: | 02.11.2018 |
| Confirmed by Study dept. on: | 27.03.2019 |
| Date and time of defence: | 27.06.2019 09:00 |
| Date of electronic submission: | 16.05.2019 |
| Date of submission of printed version: | 17.05.2019 |
| Date of proceeded defence: | 27.06.2019 |
| Opponents: | Mgr. Martin Pilát, Ph.D. |
| Guidelines |
| The goal of the thesis is to design an evolutionary optimization algorithm which - for a given machine learning task represented by a data set - finds a suitable combination of models and preprocessing methods. Student will propose a sound workflow representation, as well as other components of the evolutionary algorithm. The approach should deal with optimal hyper-parameter selection for used methods. Implementation of developed algorithms using standard machine learning libraries such as scikit-learn, and their experimental evaluation on benchmark data will be a part of the work. |
| References |
| [1] Riccardo Poli, William B. Langdon, Nicholas Freitag McPhee: A field guide to genetic programming, Published by Lulu.com, http://www.gp-field-guide.org.uk. (2008)
[2] Peter Flach: Machine Learning: The Art and Science of Algorithms That Make Sense of Data, Cambridge University Press. (2012) [3] Pavel Brazdil, Christophe Giraud-Carrier, Carlos Soares, Ricardo Vilalta: Metalearning: Applications to Data Mining. Springer. (2008) [4] Joaquin Vanschoren: Meta-Learning: A Survey. arXiv:1810.03548. (2018) |