A study of Data Mining Techniques and Challenges

Suresh Kaswan

doi:10.55524/

Authors

Suresh Kaswan Assistant Professor Department of Computer Science & Engineering, RIMT University, Mandi Gobindgarh, Punjab, India Author

DOI:

https://doi.org/10.55524/

Keywords:

Algorithms, Classification, Clustering, Data Mining, Database

Abstract

In digital era, such as now, expansion of data in databases is quite quick; everything linked to technology, such as social media, financial technology, & scientific data, all contribute significantly to data growth. Because of enormous growth of information in this age of networking & info distribution, manually evaluating, categorising, & summarising data is difficult. As a result, subjects like big data & data mining are frequently explored. Data mining is procedure for dig out info from huge amounts of data in order to create a pattern or anomaly. In order to create innovative approaches for incorporating uncertainty management into data mining, this research looks into basics of data mining as well as existing research on integrating uncertainty into data mining. Management of indeterminate data, which might be instigated by obsolete resources, specimen mistakes, or inaccurate calculations, is among most difficult issues for technologies of data mining. Development of noval approaches for adding uncertainty supervision into data mining will be a focus of future study.

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