Removing Outliers. Understanding How and What behind the Magic.

<p>An&nbsp;<a href="https://www.analyticsvidhya.com/blog/2021/05/detecting-and-treating-outliers-treating-the-odd-one-out/?utm_source=Backlink&amp;utm_medium=SEO" rel="noopener ugc nofollow" target="_blank">outlier</a>&nbsp;is any piece of data that is at abnormal distance from other points in the dataset. To us humans looking at few values at&nbsp;<em>guessing&nbsp;</em>outliers is easy.</p> <p>Take a look at this, Can you guess which are outliers?</p> <p>[25, 26, 38, 34, 3, 33, 23, 85, 70, 28, 27]</p> <p>Well my friend, here, 3, 70, 85 are outliers.</p> <p>But consider this, as a Data Scientist, we might have to analyze hundreds of columns containing thousands or even millions of values. And you will immediately come to the conclusion that this method of&nbsp;<em>guessing</em>&nbsp;is just not feasible.</p> <p><a href="https://medium.com/analytics-vidhya/removing-outliers-understanding-how-and-what-behind-the-magic-18a78ab480ff"><strong>Click Here</strong></a></p>