NOISE MINING USING MODIFIED SHARED NEAREST NEIGHBORS ALGORITHM
Removing objects that are noise is an important goal of data cleaning as noise hinders most types of data analysis. Most existing data cleaning methods focus on removing noise that is the result of low-level data errors that result from an imperfect data collection process, but data objects that are irrelevant or only weakly relevant can also significantly hinder data analysis. One of the way to enhance the data analysis as much as possible, is finding and removing the right noise data. Consequently, if the attributes for the noise can be found, a new and better way to remove the noise in a large data set can be applicated.