Data scaling is a preprocessing technique usually employed before feature selection and classification. Many artificial intelligence-based systems use features that are generated by many different feature extraction algorithms, with different kinds of sources. These features may have different dynamic ranges.
In addition, in several data mining applications with huge numbers of features with large dynamic ranges, feature scaling may improve the performance of the fitting model. However, the appropriate choice of these techniques is an important issue, since applying scaling on the input could change the structure of data and thereby affect the outcome of multivariate analysis used in data mining.
To scaling the data we will use ...
