(e.g., Gender: Male, Pregnant: Yes), missing values, etc. Analyzing data that has not been carefully screened for such problems can produce misleading results. Thus, the representation and quality of data is first and foremost before running an analysis.[1]
the training phase is more difficult. Data preparation and filtering steps can take considerable amount of processing time. Data pre-processing includes cleaning, normalization, transformation, feature extraction and selection, etc. The product of data pre-processing is the final training set. Kotsiantis et al. (2006) present a well-known algorithm for each step of data pre-processing.[2]
References
- ^ Pyle, D., 1999. Data Preparation for Data Mining. Morgan Kaufmann Publishers, Los Altos, California.
- ^ S. Kotsiantis, D. Kanellopoulos, P. Pintelas, "Data Preprocessing for Supervised Leaning", International Journal of Computer Science, 2006, Vol 1 N. 2, pp 111–117.