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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=90
k=220
chang_spiral
1.0
minPts=4
k=53
fraenti_s3
1.0
minPts=834
k=5000
bone_marrow_fixLabels
1.0
minPts=13
k=25
fu_flame
1.0
minPts=38
k=120
gionis_aggregation
1.0
minPts=79
k=630
veenman_r15
1.0
minPts=21
k=118
zahn_compound
1.0
minPts=8
k=141
synthetic_spirals
1.0
minPts=5
k=12
synthetic_cassini
1.0
minPts=238
k=214
twonorm_100d
1.0
minPts=181
k=200
twonorm_50d
1.0
minPts=19
k=200
synthetic_cuboid
1.0
minPts=1
k=54
bone_marrow
1.0
minPts=15
k=38