title: Data Standardization vs Normalization vs Robust Scaler
body: <p>I am working on data preprocessing and want to compare the benefits of <strong>Data Standardization vs Normalization vs Robust Scaler</strong> practically.</p>
  <p>In theory, the guidelines are:</p>
  <p><strong>Advantages:</strong></p>
  <ol>
  <li><em>Standardization</em>: scales features such that the distribution is centered around 0, with a standard deviation of 1.</li>
  <li><em>Normalization</em>: shrinks the range such that the range is now between 0 and 1 (or -1 to 1 if there are negative values).</li>
  <li><em>Robust Scaler</em>:  similar to normalization but it instead uses the interquartile range, so that it is robust to outliers.</li>
  </ol>
  <p><strong>Disadvantages:</strong></p>
  <ol>
  <li><em>Standardization</em>: not good if the data is not normally distributed (i.e. no Gaussian Distribution).</li>
  <li><em>Normalization</em>: get influenced heavily by outliers (i.e. extreme values).</li>
  <li><em>Robust Scaler</em>: doesn't take the median into account and only focuses on the parts where the bulk data is.</li>
  </ol>
  <hr />
  <p>I created <em>20 random</em> numerical inputs and tried the above-mentioned methods (<em>numbers in red color represent the outliers</em>):</p>
  <p><a href="https://i.stack.imgur.com/WizV0.png" rel="noreferrer"><img src="https://i.stack.imgur.com/WizV0.png" alt="Methods Comparison" /></a></p>
  <hr />
  <p>I noticed that -<em>indeed</em>- the Normalization got affected negatively by the outliers and the change scale between the new values became tiny (<em>all values almost identical -6 digits after the decimal point- <code>0.000000x</code></em>) even there is noticeable differences between the original inputs!</p>
  <p>My questions are:</p>
  <ol>
  <li>Am I right to say that also Standardization gets affected negatively by the extreme values as well? If not, why according to the result provided?</li>
  <li>I really can't see how the <em><strong>Robust Scaler</strong></em> improved the data because I still have <em><strong>extreme</strong></em> values in the resulted data set? Any simple complete interpretation?</li>
  </ol>