Clustering algorithms exist to assign observational units to relavant groups. A major problem is identifying the ideal number of groups if the true number is not known in advance.
This is the first in a series of blocks where we will create a visualization designed to help a domain expert identify the ideal number of groups for a set of time series observations.
The images above were created in R as part of the data analysis process. We'll use D3 to create an interactive version.
xxxxxxxxxx<meta charset="utf-8"><style>img { display: block;}a { display: block; }</style><h2>Income from ages 25-65</h2><img src="hdinc.png" alt="Income Series"/><h2>Group Assignment with k = 10</h2><img src="kmeans_c_10.png" alt="Clusters for K = 10"/><a href="kmeans_matrix.pdf" target="_blank">Matrix of Clusters</a>