Data Pre-processing Techniques in Data Mining: A Review

Pankaj Saraswat; Swapnil Raj

doi:10.55524/ijircst.2022.10.1.22

Abstract

Data mining is the process of finding interesting patterns and models from massive datasets. In the field of natural and physical sciences, data collection, management, and analysis have evolved as the most trustworthy source of information and emergence of new findings, information, and products. The development of the most effective procedures in statistical circumstances has therefore become standard practice in the academic and industry sectors. Under actual situations, dealing with enormous datasets, there are bound to be discrepancies and abnormalities of many types that prohibit us from knowing the true results of realistic issues. These concepts and trends are helpful in decision-making situations. The quality of the data is the most important factor in data mining. For efficient information mining, computer-based data pre-processing approaches provide methods that assist the data under processing in conforming to conventional structures, hence significantly improving the efficiency of computer algorithms.

Keywords

Data mining, Data preprocessing, Dataset pattern, Dataset, KDD, Knowledge Discovery.

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Cites this article as

P. S. , S. R. , "Data Pre-processing Techniques in Data Mining: A Review", International Journal of Innovative Research in Engineering & Management (ijircst), Vol-10, Issue-1, Page No-121-124, 2022. Available from: https://doi.org/10.55524/ijircst.2022.10.1.22

Corresponding Author

Pankaj Saraswat

Assistant Professor, Department of Computer Science Engineering, Sanskriti University, Mathura, Uttar Pradesh

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