标题：A Framework for Child Development analysis and Learning Disability Prediction using a Hybrid Naive Bayes and Decision Tree Fusion Technique – NB Tree
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2016
卷号：5
期号：7
页码：13801
DOI：10.15680/IJIRSET.2016.0507200
出版社：S&S Publications
摘要：Child development analysis has long been a research interest that seeks to understand and explain thedifferent aspects of growth, including physical, emotional, intellectual, social, perceptual and personality development.By better understanding how and why people change and grow, one can apply this knowlede to understand the needs ofa child and fulfilling them and allow them to reach their full potential. Clearly, the aim of child development is broadand the scope of the field is extensive. The research study therefore focus to apply a datamining approch to predict thechild's learning behavior and skills using machine learning algorithms. The information gained from this evaluation isfurthur used to predict learning disbility found in children. The purpose of learning disability prediction is to determinea child's strengths and weaknesses so that parents and school authorities can provide the best learning environment for achild. The observations show that the prediction model developed using a Hybrid Naive Bayes and Decision Treefusion technique-NB Tree is found to be the best among classification and prediction algorithms for child developmentanalysis and learning disability prediction.
关键词：Child development analysis; Learning disability; Naive Bayes; Decision Tree; NB Tree.
