Login for students

Login for employees

Publication detail

Reflecting on Imbalance Data Issue when Teaching Performance Measures
Authors: Škrabánek Pavel | Majerík Filip
Year: 2017
Type of publication: článek ve sborníku
Name of source: Artificial Intelligence Trends in Intelligent Systems : Proceedings of the 6th Computer Science On-line Conference 2017 (CSOC2017). Vol 1
Publisher name: Springer
Place: Heidelberg
Page from-to: 33-42
Titles:
Language Name Abstract Keywords
cze Zohlednění problematiky nevyváženosti datové sady při výuce metod určených k evaluaci binárních klasifikátorů V tomto příspěvku je představena nová metoda výuky metod určených k evaluaci binárních klasifikátorů. Tato metoda umožňuje studentům pochopit souvislosti mezi jednotlivými metrikami i příčiny jejich potencionální senzitivity na složení datové sady. Metoda byla primárně vyvinuta pro potřeby výuky na technických oborech, lze ji však snadno upravit i pro jiné obory. Své uplatnění může nalézt například v oblasti medicíny, ekonomiky, nebo sociálních věd. strojové učení, binární klasifikátor, nevyvážená datová sada, metriky pro měření výkonu, výuková metoda
eng Reflecting on Imbalance Data Issue when Teaching Performance Measures 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. machine learning; binary classification; imbalanced data; performance measures; teaching method

Department

Map

en.mapy.cz

Services

Popular Links

© 2023 University of Pardubice, Studentská 95, 532 10 Pardubice 2
Phone: +420 466 036 111, 466 036 112, 466 036 113
Webmaster, RSS
Data box ID: f5vj9hu
Accessibility Statement
CC BY-NC-ND 4.0Creative CommonsAttributionNonCommercialNoDerivatives