Prediction of Child Development using Data Mining Approach

Child development is the sector that consists of scientific research of the patterns of growth, power and change that arise from conception through adolescence. One can apply this knowledge to realize the necessities of a child by viewing how and why individuals alternate and grow. Thus, pleasing them and allowing them to arrive at their maximum capacity. The intention of this study is to research the child growth based on the features consisting of age, height and weight. In order to understand how the physical growth of child switches with time, data is gathered from various sources such as Anganwadis, Primary Schools and Primary health Centres and a data mining method is implemented to expect the child growth. In this method, assessment of two data mining approaches ID3 Decision Tree and Naïve Bayes classifier is carried out on the basis of factors such as prediction accuracy, error rate and learning time.