A Simple Interpretation of Logistic Regression Coefficients

<p>I&rsquo;ve always been fascinated by&nbsp;<strong>Logistic Regression</strong>. It&rsquo;s a fairly simple yet powerful Machine Learning model that can be applied to various use cases. It&rsquo;s been widely explained and applied, and yet, I haven&rsquo;t seen many correct and simple interpretations of the model itself. Let&rsquo;s crack that now.</p> <p>I won&rsquo;t dive into the details of what Logistic Regression is, where it can be applied, how to measure the model error, etc. There&rsquo;s already been lots of good writing about it. This post will specifically tackle&nbsp;<strong>the interpretation of its coefficients,&nbsp;</strong>in a simple, intuitive manner,<strong>&nbsp;</strong>without introducing unnecessary terminology.</p> <p><a href="https://towardsdatascience.com/a-simple-interpretation-of-logistic-regression-coefficients-e3a40a62e8cf"><strong>Read More</strong></a></p>