Reflecting on Imbalance Data Issue when Teaching Performance Measures

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F17%3A39902712" target="_blank" >RIV/00216275:25530/17:39902712 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-57261-1_4" target="_blank" >http://dx.doi.org/10.1007/978-3-319-57261-1_4</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-57261-1_4" target="_blank" >10.1007/978-3-319-57261-1_4</a>

Result language
angličtina
Original language name
Reflecting on Imbalance Data Issue when Teaching Performance Measures
Original language description
Importance of soft computing methods has continuously grown for many years. Particularly machine learning methods have been paid considerable attention in the business sphere and subsequently within the general public in the last decade. Machine learning and its implementation is the object of interest of many commercial subjects, whether they are small companies or large corporations. Consequently, well-educated experts in the area of machine learning are highly sought after on the job market. Most of the technical universities around the world have incorporated the machine learning into their curricula. However, machine learning is a dynamically evolving area and the curricula should be continuously updated. This paper is intended to support this process. Namely, an imbalance data issue, in context of performance measures for binary classification, is opened, and a teaching method covering this problem is presented. The method has been primary designed for undergraduate and graduate students of technical fields; however, it can be easily adopted in curricula of other fields of study, e.g. medicine, economics, or social sciences.
Czech name
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Czech description
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Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
50302 - Education, special (to gifted persons, those with learning disabilities)

Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Artificial Intelligence Trends in Intelligent Systems : Proceedings of the 6th Computer Science On-line Conference 2017 (CSOC2017). Vol 1
ISBN
978-3-319-57261-1
ISSN
—
e-ISSN
neuvedeno
Number of pages
10
Pages from-to
33-42
Publisher name
Springer
Place of publication
Heidelberg
Event location
Zlín
Event date
Jun 26, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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