Assessing smallest clusters

In this exercise you're going to have a look at the clusters that came out of DBSCAN, and flag certain clusters as fraud:

• you first need to figure out how big the clusters are, and filter out the smallest
• then, you're going to take the smallest ones and flag those as fraud
• last, you'll check with the original labels whether this does actually do a good job in detecting fraud.

Available are the DBSCAN model predictions, so n_clusters is available as well as the cluster labels, which are saved under pred_labels. Let's give it a try!