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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=43
k=228
chang_spiral
1.0
minPts=6
k=35
fraenti_s3
1.0
minPts=1000
k=5000
bone_marrow_fixLabels
1.0
minPts=13
k=25
fu_flame
1.0
minPts=1
k=64
gionis_aggregation
1.0
minPts=289
k=709
veenman_r15
1.0
minPts=12
k=155
zahn_compound
1.0
minPts=304
k=399
synthetic_spirals
1.0
minPts=155
k=250
synthetic_cassini
1.0
minPts=119
k=226
twonorm_100d
1.0
minPts=86
k=200
twonorm_50d
1.0
minPts=54
k=200
synthetic_cuboid
1.0
minPts=1
k=8
bone_marrow
1.0
minPts=8
k=34