Data preprocessing: Difference between revisions

Revision as of 20:53, 11 December 2023

Revision as of 20:53, 11 December 2023

Line 1:

{{Citations needed|date=August 2023}}

'''Data preprocessing''' can refer to manipulation, filtration or augmentation of data before it is analyzed,<ref>{{Cite web|title=Guide To Data Cleaning: Definition, Benefits, Components, And How To Clean Your Data|url=https://www.tableau.com/learn/articles/what-is-data-cleaning|access-date=2021-10-17|website=Tableau|language=en-US}}</ref> and is often an important step in the [[data mining]] process. The phrase [[GIGO|"garbage in, garbage out"]] is particularly applicable to [[data mining]] and [[machine learning]] projects. [[Data collection]] methods are often loosely controlled, resulting in out-of-range values, impossible data combinations, and [[missing values]], amongst other issues.

Analyzing data that has not been carefully screened for such problems can produce misleading results. Thus, representation and [[data quality|quality of data]] is necessary before running any analysis.<ref>Pyle, D., 1999. ''Data Preparation for Data Mining.'' Morgan Kaufmann Publishers, [[Los Altos, California]].</ref>