Check the Quality

Now that we have trained our clustering algorithm we have to evaluate its performances to assess the results.

Methods description

• .labels_: This attribute of the KMeans object contains the cluster labels assigned to each data point after fitting the KMeans algorithm to the data;
• y == labels: This is a comparison operation that checks element-wise equality between two arrays y and labels, resulting in a boolean array;
• correct_labels: This variable stores the count of data points that were correctly labeled, i.e., assigned to the correct cluster.