@inproceedings{4f9524b1f7cb4312abb5937274505358,
title = "Evaluating importance for numbers of bins in discretised learning and test sets",
abstract = "The paper presents research on the influence of the numbers of bins, found for attributes in supervised discretisation for input sets, on classifiers performance. Firstly, the variables were divided into categories defined by numbers of bins, and for these categories several decision systems were tested. Secondly, for features with single bins, unsupervised discretisation was executed and the resulting performance studied. The experiments show usefulness of characterisation of variables by numbers of bins, and cases of improvement of solutions by combining supervised with unsupervised discretisation.",
keywords = "Attribute, Bin, Classification, Supervised discretisation, Unsupervised discretisation",
author = "Urszula Sta{\'n}czyk",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2018.; 9th KES International Conference on Intelligent Decision Technologies, KES-IDT 2017 ; Conference date: 21-06-2017 Through 23-06-2017",
year = "2018",
doi = "10.1007/978-3-319-59421-7\_15",
language = "English",
isbn = "9783319594200",
series = "Smart Innovation, Systems and Technologies",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "159--169",
editor = "Howlett, \{Robert J.\} and Jain, \{Lakhmi C.\} and Jain, \{Lakhmi C.\} and Ireneusz Czarnowski and Howlett, \{Robert J.\} and Jain, \{Lakhmi C.\}",
booktitle = "Intelligent Decision Technologies 2017 - Proceedings of the 9th KES International Conference on Intelligent Decision Technologies, KES-IDT 2017",
address = "Germany",
}