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IJET International Journal of Engineering and Technology E-ISSN 2227-524X

Data Analytics: Why Data Normalization

Abstract

The two maestros Artificial Intelligence and Machine learning are ruling the data filled world with good analytics. Many of these domain skills are used in the industry to analyze and interpret the data beyond what it actually is. Supporting the known saying find the horse before the cart is ready is what it mean to normalize the data before getting it analyzed. This article focus on what normalization actually is, why normalization is needed before data analysis and how data normalization is done.

Authors and Affiliations

  • Dr. K. Dhana Sree
  • Dr. C. Shoba Bindu

About this article

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Keywords

  • The two maestros Artificial Intelligence and Machine learning are ruling the data filled world with good analytics. Many of these domain skills are used in the industry to analyze and interpret the data beyond what it actually is. Supporting the known say

References

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[5] Ismail Bin Mohamad, Dauda Usman. “Standardization and Its Effects on K-Means Clustering Algorithm”. Research Journal of Applied Sciences, Engineering and Technology. Vol 6 (17), 3299-3303, 2013.

[6]https://www.epa.gov/sites/production/files/2016-06/documents/normality.pdf

[7] K. Y. Yeung W. L. Ruzzo. “Principal component analysis for clustering gene expression data”. Bioinformatics, Vol 17 (9), 763–7741, Sep 2001,


How to Cite

K. Dhana Sree, D., & C. Shoba Bindu, D. (2018). Data Analytics: Why Data Normalization. International Journal of Engineering and Technology, 7(4.6), 209-213. https://doi.org/10.14419/ijet.v7i4.6.20464