Dyslexia Prediction Using Machine Learning

Dyslexia is a learning disorder or issue characterized by a lack of reading and /or writing skills, difficulty in word naming, and poor spelling. Dyslexia can be recorded into two different ways, surface, and phonological dyslexia. The test of perusing the word is surface dyslexia, while phonological dyslexia is the issue of investigating a part of a word. Researchers are intrigued primarily in phonological dyslexia since it is more extreme. A kid can read and show indicators of reading problems most of the time, and dyslexia is recognized. If phonological indicators are used to diagnose the disease before a kid can read it, it would have substantial advantages for early reading. The current effort aims to produce a software tool that parents may use before their children can determine if a child's dyslexia is in danger. In this, the techniques used are SVM, Grid search CV with an accuracy of 97.42%. We have improved the accuracy in predicting dyslexia by using conventional methodologies of predicting dyslexia.