Evaluation of the Bias of Student Performance Data with Assistance of Expert Teacher
Autor: | Pablo Pytel, María Florencia Pollo-Cattaneo, Luciano Straccia, Cinthia Vegega |
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Rok vydání: | 2018 |
Předmět: |
Training set
Work (electrical) Computer science Order (business) 020204 information systems 0202 electrical engineering electronic engineering information engineering Intelligent decision support system 020207 software engineering 02 engineering and technology Education and technology Complex problems Data science Domain (software engineering) |
Zdroj: | Communications in Computer and Information Science ISBN: 9783030015343 ICAI |
DOI: | 10.1007/978-3-030-01535-0_2 |
Popis: | Machine Learning algorithms have many advantages and a great potential for solving complex problems in different domains. However, it is not “magical”. One of its main difficulties lies in recollecting representative data of the domain in order to train the system, otherwise, its efficacy will be seriously compromised. Therefore, a method has been proposed to evaluate the collected data with the assistance of the available domain experts and determine whether it can be used. In this work, the method is applied to evaluate two versions of data gathered on the students’ performance in an undergraduate program course. As a result, it is determined whether they can be used in the training of an Intelligent System that will foretell such performance. |
Databáze: | OpenAIRE |
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