Abstract
Nowadays the amount of data that is collected in various settings is growing rapidly. These elaborate data records enable the training of machine learning models that can be used to extract insights and for making better informed decisions. When doing the data mining task, on one hand, feature selection is often used to reduce the dimensionality of the data. On the other hand, we need to decide the structure (parameters) of the model when building the model. However, feature selection and the parameters of the model may interact and affect the performance of the model. Therefore, it is difficult to decide the optimal parameter and the optimal feature subset without an exhaustive search of all the combination of the parameters and the feature subsets which is time-consuming. In this paper, we study how the interaction between feature selection and the parameters of a model affect the performance of the model through experiments on four data sets.
Original language | English |
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Title of host publication | Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications - 17th International Conference, IPMU 2018, Proceedings |
Subtitle of host publication | 17th International Conference, IPMU 2018, Cádiz, Spain, June 11-15, 2018, Proceedings, Part III |
Editors | J. Medina, I. Perfilieva, R.R. Yager |
Place of Publication | Dordrecht |
Publisher | Springer |
Pages | 150-161 |
Number of pages | 12 |
ISBN (Electronic) | 978-3-319-91479-4 |
ISBN (Print) | 978-3-319-91478-7 |
DOIs | |
Publication status | Published - 1 Jan 2018 |
Event | 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2018) - Cadiz, Spain Duration: 11 Jun 2018 → 15 Jun 2018 Conference number: 17 |
Publication series
Name | Communications in Computer and Information Science |
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Volume | 855 |
ISSN (Print) | 1865-0929 |
Conference
Conference | 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2018) |
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Abbreviated title | IPMU 2018 |
Country/Territory | Spain |
City | Cadiz |
Period | 11/06/18 → 15/06/18 |
Funding
Acknowledgement. This work is partially supported by Philips Research within the scope of the BrainBridge Program.
Keywords
- Feature selection
- Fuzzy models
- Model parameters
- Number of clusters