Analysis with K-means Lab

According to ABC news, China has the highest concentration of hackers in the world. Having the ability to discover patterns in data may prevent future attacks and provide the capability to discover attacker affiliations. K-means is an unsupervised learning method that is used to find similarities in unlabeled data. Its goal is to group data based on commonalities in data structure. The resulting groups (clusters) can then be applied to others models to make predictions. In this lab, we are going illustrate how to classify data using k-means.