Principle, Methodology and Application for Data Cleaning techniques

Con-temporarily, information data has become the cornerstone of every company’s decision-making. In a vast flow information, choosing right is first step in developing successful predictions. After determinations requirements, analysis purpose and prediction direction, outlier processing, missing value processing repeated are usually encountered. This paper introduces limitations, advantages disadvantages different methods application detail. At same time, this some interpolation based on mathematical statistics, such as thermal interpolation, Lagrange Newton interpolation. it also provides normal distribution method which better dealing with problems, popular K-nearest neighbor algorithm. Finally, illustrates logic diagram cleaning preparation stage. Overall, these results offer guideline for selecting appropriate treatment corresponding situation during process.