Classification of Data Using Semi-Supervised Learning (A Learning Disability Case Study)

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Provided by: International Association of Engineering and Management Education (IAEME)
Topic: Big Data
Format: PDF
In classification, Semi-supervised learning occurs when a large amount of unlabeled data is available. In such a situation, how to enhance predictability of classification through unlabeled data is the focus. In this paper, the authors propose a methodology based on Support Vector Machine of semi-supervised learning and implement it on the case samples of learning disability. It is observed that about 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to be identified in elementary school where there is no one sign to be identified.
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