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clustering evaluation framework
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HDBSCAN
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Best Parameters
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Best Qualities
Best Parameters
Hints:
Which parameter sets lead to the optimal clustering quality?
Please choose a clustering quality measure:
Davies Bouldin Index (R)
Dunn Index (R)
F1-Score
F2-Score
False Discovery Rate
False Positive Rate
Fowlkes Mallows Index (R)
Jaccard Index (R)
Rand Index
Rand Index (R)
Sensitivity
Silhouette Value (R)
Specificity
V-Measure
Dataset
Best quality
Parameter set
chang_pathbased
0.848
minPts=9
k=24
chang_spiral
0.938
minPts=5
k=34
fraenti_s3
0.947
minPts=4
k=2033
bone_marrow_fixLabels
0.809
minPts=11
k=23
fu_flame
0.956
minPts=2
k=12
gionis_aggregation
0.959
minPts=8
k=95
veenman_r15
0.993
minPts=2
k=39
zahn_compound
0.98
minPts=2
k=56
synthetic_spirals
1.0
minPts=6
k=2
synthetic_cassini
0.893
minPts=6
k=41
twonorm_100d
0.507
minPts=1
k=76
twonorm_50d
0.512
minPts=73
k=113
synthetic_cuboid
1.0
minPts=8
k=4
bone_marrow
0.797
minPts=9
k=23