A new approach of controlled binning for data smoothening

Binning is a process of noise removal from data. It is an important step of preprocessing where data smoothening occurs by computation of the data points. The knowledge which is to be extracted from the data is very crucial which demands for a control in the loss of data. We have developed a method by which the user can control the level of data smoothening by binning. The acceptable loss percentage on individual data points is asked from the user. Allowable loss is calculated and a decision is made to smoothen the value or retain it .Our proposed method will let the user get a requirement based output. Our proposed algorithm will allow the user to interact with the data preprocessing system unlike the older algorithms. Different stages of smoothened outputs are obtained by different loss percentages. This preprocessed output produced will be of a better quality and will resemble more to the real world data.