The data is 2d : the two parameters are error and time. I tried using the following clustering algorithms: 1) kmeans:clusters are spherical. This algo clustered as follows:. Kmeans did form clusters as needed. 2)dbscan: problem- I have clusters of varying density. It assigned every data point to noisy cluster I.e. it assigned a label of -1 to every point. 3) GMM: this also did not cluster the data points as needed. It performed clustering similar to kmeans. 4)affinity propagation is throwing a memory error.
Can someone please suggest a way of assigning different labels to each of the visually separable cluster.