Building the Model

Creating a model

The create_model() function lets us easily create and evaluate the clustering model of our preference such as the k-means algorithm. This function creates $4$ clusters by default. We can set the num_clusters parameter to $3$ because this is the correct number. Instead of doing that, however, we’ll follow an approach that generalizes for real-world datasets where the cluster number is typically unknown. After executing the function, we print several performance metrics such as silhouette, Calinski-Harabasz, and Davies-Bouldin. We’ll focus on the silhouette coefficient defined in the following equation.

$$s(i)=\frac{b(i)-a(i)}{\max \{a(i), b(i)\}}$$

$$-1 \leq s(i) \leq 1$$

• $s(i)$ is the silhouette coefficient of the dataset instance $i$.
• $a(i)$ is the mean intra-cluster distance of $i$.
• $b(i)$ is the mean nearest-cluster distance of $i$.