This week lesson is about learning from observation. More like about clustering information. Clustering can depends on various information, gender, occupation, heredity(biologically), or how they look(species).

For an information, there can be multiple cluster, but which information belong to which cluster need to be calculated. To calculate which information belong to which cluster, in a graph, the calculation for each information to the main cluster need to be calculated. And the every information will be closer to one cluster than the other. The way the distance is calculated is using euclidean or manhattan method.

After calculating the distance of information to cluster(s), finding the mean coordinates of the cluster is necessary. And then recalculating the distance again, until the coordinates of the cluster is not changing nor the information related to the cluster.

As for the project, further discussion have not yet been held.