Finding the Missing Data to Detect Patterns using Data Mining

Umamaheswari. D; Shyamala. N

CALL FOR PAPERS : Mar-2023

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25-Mar-23

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Finding the Missing Data to Detect Patterns using Data Mining

Author(s):

Umamaheswari. D , NGM COLLEGE; Shyamala. N, NGM COLLEGE

Keywords:

Patterns, Pattern Prediction, Regression, Sequencing, Characterization, Comparison

Abstract:

Data mining refers to the extracting or “mining” knowledge from large amount of data. The process of performing data analysis may uncover important data patterns, contributing greatly to business strategies, knowledge bases, and scientific and medical research. The exploration and analysis, by automatic or semiautomatic means, of large quantities of data in order to discover meaningful patterns and rules. The rules include the iterative process of detecting and extracting patterns from large databases. This paper helps us to identify “signatures” hidden in large databases, as well as learn from repeated examples. The extraction of implicit, previously unknown, and potentially useful information from data is the ultimate goal of any statically viable approach. Strong patterns, if found, will likely generalize to make accurate predictions on future data. Data Mining automates the detection of relevant patterns in databases. The Pattern finding is applied for disguised bank details and complete result is expected.