A Survey on ADHD using Data Mining Techniques
DOI:
https://doi.org/10.26438/ijcse/v6si8.3033Keywords:
KD, ADHD, DataNormalization, Datamining, ClassificationAbstract
The thriving medical applications of Data mining in the field of medicine and public health led to the popularity of its use in KDD (Knowledge Discovery in Data Mining.). Disease diagnosis is one of the applications in the medical field. Data Mining tools are establishing the successful result in ADHD. This survey paper reveals Attention Deficit Hyper Active Disorder (ADHD) is a pattern of behaviour that affects approximately 3 to 5% of school going population. This paper surveys on implementation methods by using well known Data Mining techniques. Data Mining provides the methodology and technology to transform these mounds of data into useful information for decision making. The aim of this survey is to predict ADHD problems using Data Mining techniques like classification, Clustering, AI Neural networks, Bayesian Classifiers and Decision Trees. To implement these classification techniques different sources and methods of data collection, data set, data distribution and normalization are required .Therefore this paper aims to understand about Mining and its importance in Psychology
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