Stop Using Elbow Diagram To Find Best K-Value And Use This Instead

K-Means is one of the most important clustering algorithms that are usually used by data scientists and machine learning practitioners in unsupervised learning tasks. One of the parameters for this algorithm that needs to be handled carefully is the number of clusters K. The most popular method to find the optimal value of K is the elbow diagram, however, it is not the most effective method to do so. In this article, we will explore more effective methods to find the optimal K- value for the K-Means clustering algorithm.