Childhood obesity is a very worrying global epidemic and the Malaysian children have shown alarming statistics. Therefore, obesity and overweight predictions at an early age are important. This paper presents performances of eleven data mining techniques, that are sensitivity, specificity
and accuracy tested using 320 Malaysian children datasets that were collected. The data mining techniques are decision tree, Support Vector Machine, Neural Networks, Discriminant Analysis, K-means Clustering, Regression and Naϊve Bayes. The results indicated that the Classification
and Regression Tree has shown high specificity in normal and obesity predictions, while the Naive Bayes has shown high sensitivity in overweight and obesity predictions. Meanwhile, other techniques have adequate or poor accuracy. Overall, the data mining techniques accuracy can be improvised.
Previous studies also indicated that the data mining techniques have limited prediction accuracy. Therefore, based on analysis, the data mining techniques can be enhanced to address the issue of low prediction accuracy for childhood obesity and overweight predictions.
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Document Type: Research Article
Faculty of Science and Information Technology, Universiti Teknologi PETRONAS, Bandar Seri Iskandar 31750, Perak, Malaysia
School of Computer Sciences, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia
College of Computer and Information System, Department of Computer Sciences, Pricenss Noura Bint Abdulrahman University, Riyadh, Kingdom of Saudi Arabia
Publication date: 01 October 2018
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ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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