In this thesis, a treemap-based interactive clustering algorithm is implemented and evaluated. The treemap's rectangles present scatterplots of dimensionally reduced renderings of clusters. Based on the visual representation, a user makes decisions on splitting clusters with a user-selectable clustering algorithm like k-means or hierarchical clustering. This thesis shows that this implementation is practical for finding hierarchical clusters in the MNIST database. The thesis also demonstrates the possibility of finding sub-clusters within the clusters of the individual digits.