Unsupervised Learning: Building Score Metrics for Cluster Points

Clustering is an unsupervised machine learning technique used for discovering interesting patterns in data. An example would be grouping similar customers based on their behavior, building a spam filter, identifying fraudulent or criminal activity. In Clustering, similar items (or data points) are grouped together. However, we do not only want to group similar items together, we would also like to measure how similar or different they are. To solve this, we can easily create a scoring algorithm.