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The application of active learning in identification of students with financial difficulties

Published: 20 December 2017 Publication History

Abstract

The previous classifiers tend to achieve unsatisfied performance with class-imbalanced data. In order to identify the poverty students using data with few labels, we adopted the active learning method. The results show that it can get lower error compared with the random sampling strategy, which means that the strategy applied in our problem is effective. With the strategy, we can classify the poverty students with much more accuracy, which is useful in distributing subsidies to students in college.

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  • (2024)Active-Learning Method: An Effective Way to Generate Ground Truth Data to Test & Validate ADAS Function DevelopmentSAE Technical Paper Series10.4271/2024-26-0364Online publication date: 23-Jan-2024

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    ICETC '17: Proceedings of the 9th International Conference on Education Technology and Computers
    December 2017
    270 pages
    ISBN:9781450354356
    DOI:10.1145/3175536
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    Published: 20 December 2017

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    Author Tags

    1. Active Learning
    2. imbalanced classification
    3. poverty student identification

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    • (2024)Active-Learning Method: An Effective Way to Generate Ground Truth Data to Test & Validate ADAS Function DevelopmentSAE Technical Paper Series10.4271/2024-26-0364Online publication date: 23-Jan-2024

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