Figure 2.
The image displays a graph indicating the relationship between inertia, represented on the vertical axis, and k values on the horizontal axis. The vertical axis ranges from zero to approximately one hundred and thirty, while the horizontal axis extends from zero to about eighteen. The plotted data points create a downward curve, demonstrating a decrease in inertia as k increases. One specific data point is highlighted in red, indicating its particular significance within the dataset, while the rest of the points are shown in blue. The graph includes an axis grid for better readability and analysis.The elbow-method is used to select the number of clusters for the K-means algorithm
Note(s): As no formal definition of the “elbow-point” exists, the method is considered to be subjective. Nevertheless, due to the simplicity and intuition, this approach is often applied. The elbow-method selects by finding a compromise between the quality of the clustering and over-fitting. The value is chosen to be , resulting in 7 distinct clusters
Source: Authors’ own work