A Study of dyslexia using different machine learning algorithm with data mining techniques
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https://doi.org/10.14419/ijet.v7i4.21691 -
Abstract
There are many children’s were affected by dyslexia problem over the world. This paper is focusing on medical diagnostic problem – detecting and diagnosing children who were affected by dyslexia based on checklist containing the symptoms and signs of dyslexia using Artificial Neural Network techniques applied with WEKA. Many researchers research identifying or diagnosing dyslexia or non-dyslexia children in many ways. But the drawback in the existing system is they are research based on either Intellectual Intelligent (IQ) or Emotion-al Intelligent (EQ). They are not given accurate result for detecting the dyslexia children. The person’s achievement in life is depends upon both knowledgeable and emotional intelligence. IQ is not only giving successful in life. We must need EQ also. The aim of the present research is to propose a quicker and more efficient technique of diagnosing the problem, leading to timely treatment of the children.
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How to Cite
H, S., & S, S. M. (2018). A Study of dyslexia using different machine learning algorithm with data mining techniques. International Journal of Engineering & Technology, 7(4), 3406-3411. https://doi.org/10.14419/ijet.v7i4.21691Received date: 2018-11-26
Accepted date: 2018-11-26