The Data Mining Measures: An Effective Decision Making Analysis

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Authors

  • Minakshi .
  • Dr. Kalpana .

Keywords:

Data Mining, Measures, Decision Making, Analysis, Knowledge Discovery, Prediction, Affiliation Rules Mining, Collinearity, Interrelations

Abstract

Data Mining is regularly used to apply to the two separate procedures of Knowledge Discovery and Prediction. Learning Discovery gives express data about the attributes of the gathered data utilizing various procedures like affiliation governs mining.Data mining is typically performed on genuine data. Such data are defenceless against collinearity on account of obscure and conceivably surreptitiously interrelations. An unavoidable reality of Data Mining is that the (sub) set of data being examined may not be illustrative of the entire area, and subsequently may not contain cases of certain basic connections that exist crosswise over different parts of the space.

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Published

2017-04-01

How to Cite

[1]
“The Data Mining Measures: An Effective Decision Making Analysis: -”, JASRAE, vol. 13, no. 1, pp. 506–510, Apr. 2017, Accessed: Jul. 23, 2025. [Online]. Available: https://ignited.in/index.php/jasrae/article/view/6588

How to Cite

[1]
“The Data Mining Measures: An Effective Decision Making Analysis: -”, JASRAE, vol. 13, no. 1, pp. 506–510, Apr. 2017, Accessed: Jul. 23, 2025. [Online]. Available: https://ignited.in/index.php/jasrae/article/view/6588