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Use HMM and KNN for Classifying Corneal Data  

Payam Porkar Rezaeiye*1, Mehrnoosh Bazrafkan2, Ali Akbar movassagh 3,  Mojtaba Sedigh Fazli4, Gholam hossein bazyari5

*1 Department of Computer, Damavand Branch, Islamic Azad University, Damavand, Iran, Email:porkar@damavandiau.ac.ir

2Marvdasht Branch,Islamic Azad University, Zarghan,Iran, Email : mehrnoosh.bazrafkan@gmail.com
 3
Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran, Email : a.movassagh@gmail.com

4Department of Computer, Damavand Branch, Islamic Azad University, Damavand, Iran, Email : Mojtabafazli@yahoo.com

5Varamin University of Science and Technology, Varamin, Iran, Email : bazyari@gmail.com

 
Abstract .These days to gain classification system with high accuracy that can classify complicated pattern are so useful in medicine and industry. In this article a process for getting the best classifier for Lasik data is suggested. However at first it's been tried to find the best line and curve by this classifier in order to gain classifier fitting, and in the end by using the Markov method a classifier for topographies is gained. What are mentioned in this article are supposed to gain a strong classifier so that under Marko theory can choose eyes appropriate for corneal graft.
 
Keywords : HMM, KNN, classification, topography, corneal.
 URL: http://dx.doi.org/10.7321/jscse.v3.n3.134  
 
 

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