Laboratory for Machine Learning and Knowledge Representation
Development of machine learning algorithms and their applications in data mining and knowledge discovery tasks.
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The Laboratory works on scientific research in the field of technical sciences and specifically on:
- research and development of machine learning algorithms and their application in data analysis
- theory and application of knowledge representation and reasoning algorithms
- development of numerical algorithms for modeling of complex systems
Currently we work on:
- development of algorithms for rule induction from large datasets
- evaluation of outlier detection algorithms and development of a new approach based on random forests
- data mining in social applications (political instability, direct foreign investment, international tourism industry)
- detection of subgroups of patients by mining gene expression data
- medical and technical ontologies as well as representation and reasoning for procedural knowledge
- evaluation of the quality of computational annotations in the gene ontology
- development and application of the GMDH based modeling
- development of surrogate models of the reduced complexity for embedded computer systems