Here are some brief introductions for the methods in the data preprocessing step. Data cleaning is the process of detecting, correcting or removing the inaccurate records from data;[4] Data normalization is the process used to standardize the range of independent variables or features of data;[5] Data transformation is the process of converting data from a format to the new format people expect;[6] Feature extraction is the process of transforming the input data into a set of features which can very well represent the input data.[7]