Fig. 5
From: Graph-based data clustering via multiscale community detection
The multiscale character of Markov Stability alleviates the sensitivity to the parameters of graph construction. Using the same synthetic dataset as in Fig. 3, MS finds the robust partitions and scales in the data (c=3 and c=9) in an unsupervised manner for CkNN graphs constructed with a range sparsities as given by varying the parameters: k=7 and δ=1.5,1.8,2.4 in (a), (b) and (c), respectively. Markov time, as a resolution parameter, allows the community algorithm to reveal the local and global properties of the graph constructed from the data