Fig 1.
Simulated data generated under scheme 1 with true clusters.
Fig 2.
Outcome of different clustering algorithms on simulated data generated under scheme 1.
Fig 3.
Simulated data generated under scheme 2 with true clusters.
Fig 4.
Outcome of different clustering algorithms on simulated data generated under scheme 1.
Table 1.
Accuracy, precision and recall of different clustering algorithms on data generated under scheme 1.
Table 2.
Accuracy, precision and recall of different clustering algorithms on data generated under scheme 2.
Fig 5.
Plot of accuracy, precision and recall of different clustering algorithms on data generated under scheme 1.
Fig 6.
Plot of accuracy, precision and recall of different clustering algorithms on data generated under scheme 2.
Fig 7.
T-SNE plot of data with p = 5 and k = 6.
Fig 8.
T-SNE plot of data with p = 100 and k = 6.
Fig 9.
Mean accuracy of hard DMM 1 with 2 clusters and varied dimensions.
Fig 10.
Mean accuracy of hard DMM 1 with 3 clusters and varied dimensions.
Fig 11.
Mean accuracy of hard DMM 1 with 4 clusters and varied dimensions.
Fig 12.
Mean accuracy of hard DMM 1 with 5 clusters and varied dimensions.
Fig 13.
Mean accuracy of hard DMM 1 with 6 clusters, varied dimensions and increasing overlap.
Table 3.
Mean accuracy of hard DMM 1 with varied dimensions and number of clusters.
Fig 14.
T-SNE plot of wholesale customer data.
Table 4.
Summary statistics of wholesale customers data.
Table 5.
Performance comparison of different model based clustering methods on wholesale customers data.
Fig 15.
Plot of accuracy, precision and recall of different algorithms on on wholesale customers data.
Fig 16.
T-SNE plot of wine data.
Table 6.
Summary statistics of wine data.
Table 7.
Performance comparison of different model based clustering methods on wine data.
Fig 17.
Plot of accuracy, precision and recall of different algorithms on on wine data.