Data Analytics: Why Data Normalization

 
 
 
  • Abstract
  • Keywords
  • References
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  • 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.

     

     


  • 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


      [1] SB Kotsiantis, D Kanellopoulos, PE Pintelas.”Data preprocessing for supervised learning“. International Journal of Computer Science. Vol 1 (2), 111-117.

      [2] S Patro, KK Sahu.”Normalization: A Preprocessing Stage”. arXiv preprint arXiv:1503.06462

      [3] L Al Shalabi, Z Shaaba. “Data Mining: a preprocessing Engine”. Journal of Computer Science. Vol 2 (9), 735-739, 2006.

      [4] H.E.Barbaree, D.J.K.Mewhort. “The effects of the z-score transformation on measures of relative erectile response strength: A re-appraisal”. Journal of behavior research therapy. Vol 32 (5), 547-558, June 1994.

      [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,


 

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Article ID: 20464
 
DOI: 10.14419/ijet.v7i4.6.20464




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