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    <title>statistics on Sadman Kabir Soumik</title>
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    <description>Recent content in statistics on Sadman Kabir Soumik</description>
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    <copyright>Copyright © 2022, Sadman Kabir Soumik</copyright>
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      <title>Understanding the Role of Data Normalization and Standardization in Machine Learning</title>
      <link>https://blog.sksoumik.com/artificial-intelligence/data-normalization-vs-standardization-machine-learning/</link>
      <pubDate>Sat, 12 Mar 2022 00:00:00 +0000</pubDate>
      
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            Why do we scale features? For machine learning, every dataset does not require feature scaling, and it is only needed when features have different ranges.
For example, consider a data set containing two features, age(x1) and income(x2), where age ranges from 0–100, while income ranges from 0–20,000 and higher. Income is about 1,000 times larger than age and ranges from 20,000–500,000. So, these two features are in very different ranges. When we do further analysis, like multivariate linear regression, the attributed income will influence the result more due to its larger value.
          
          
        
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