Abstract

The classifications of uncertain data become one of the tedious processes in the data-mining domain. The uncertain data are contains tuples with different data and thus to find similar class of tuples is a complex process. The attributes which have a higher level of uncertainty needs to be treated differently as compared to the attributes having lower level of uncertainty. Different algorithms exist in literature for users to choose a suitable one as per their need. This research paper deals with the fundamentals of various existing data classification techniques for uncertain data using the k nearest neighbor approach. The literature shows that much work has been done in this area but still there are certain performance issues in the k nearest neighbor classifier. K nearest neighbor is one of the important algorithms in top 10 data mining algorithms.

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