• WEIGHTED AVERAGE CLOSEST FIT APPROACH TO HANDLE MISSING VALUES

Abstract

Data preparation for data mining is a fundamental stage of data analysis. Data with missing values complicates both the data analysis and final result. It also affects loss of accuracy of mediatory result and calculations. To overcome this situation some sort of applied statistical techniques are required to employ during the data preparation. With the help of statistical methods and techniques, we can recover incompleteness of missing data and reduce ambiguities. In this paper, we introduce weighted average based sequential method by which missing attribute values are recovered.