Data preprocessing: Difference between revisions

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If there is much irrelevant and redundant information present or noisy and unreliable data, then [[knowledge discovery]] during the training phase is more difficult. Data preparation and filtering steps can take considerable amount of processing time. Data pre-processing includes [[Data cleaning|cleaning]], [[data normalization|normalization]], [[data transformation|transformation]], [[feature extraction]] and [[Feature selection|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.<ref>S. Kotsiantis, D. Kanellopoulos, P. Pintelas, "Data Preprocessing for Supervised Learning", ''International Journal of Computer Science'', 2006, Vol 1 N. 2, pp 111–117.</ref>

==See also==

*[[Data cleansing]]

*[[Data editing]]

*[[Data reduction]]

*[[Data wrangling]]

==References==