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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
0.704
minPts=5
k=7
chang_spiral
0.798
minPts=5
k=34
fraenti_s3
0.605
minPts=92
k=2054
bone_marrow_fixLabels
0.645
minPts=2
k=5
fu_flame
0.822
minPts=2
k=12
gionis_aggregation
0.844
minPts=47
k=28
veenman_r15
0.961
minPts=2
k=39
zahn_compound
0.843
minPts=2
k=56
synthetic_spirals
1.0
minPts=6
k=2
synthetic_cassini
0.718
minPts=6
k=41
twonorm_100d
0.231
minPts=133
k=200
twonorm_50d
0.231
minPts=19
k=200
synthetic_cuboid
1.0
minPts=2
k=4
bone_marrow
0.583
minPts=8
k=23