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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
1.0
minPts=210
k=1
chang_spiral
1.0
minPts=60
k=1
fraenti_s3
1.0
minPts=2500
k=1
bone_marrow_fixLabels
1.0
minPts=13
k=1
fu_flame
1.0
minPts=176
k=1
gionis_aggregation
1.0
minPts=788
k=1
veenman_r15
1.0
minPts=172
k=1
zahn_compound
1.0
minPts=1
k=19
synthetic_spirals
1.0
minPts=44
k=1
synthetic_cassini
1.0
minPts=92
k=9
twonorm_100d
1.0
minPts=140
k=7
twonorm_50d
1.0
minPts=13
k=1
synthetic_cuboid
1.0
minPts=8
k=2
bone_marrow
1.0
minPts=1
k=2