Use HMM and KNN for Classifying Corneal Data

Payam Porkar Rezaeiye; Mehrnoosh Bazrafkan; Ali Akbar Movassagh; Mojtaba Sedigh Fazli; Gholam Hossein Bazyari

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Use HMM and KNN for Classifying Corneal Data

机译：使用HMM和KNN对角膜数据进行分类

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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.

机译：这些天来获得可以对复杂模式进行分类的高精度分类系统在医学和工业中非常有用。在本文中，提出了一种获取最佳Lasik数据分类器的过程。但是，首先尝试通过该分类器找到最佳的直线和曲线，以实现分类器拟合，最后使用马尔可夫方法获得地形的分类器。本文中提到的内容应该获得强分类器，以便在Marko理论下可以选择适合于角膜移植的眼睛。

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《International Journal of Soft Computing and Software Engineering》 |2013年第3期|共9页
作者
Payam Porkar Rezaeiye; Mehrnoosh Bazrafkan; Ali Akbar Movassagh; Mojtaba Sedigh Fazli; Gholam Hossein Bazyari;
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中图分类计算技术、计算机技术;
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Use HMM and KNN for Classifying Corneal Data

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