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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=260
k=1
chang_spiral
1.0
minPts=125
k=1
fraenti_s3
1.0
minPts=715
k=239
bone_marrow_fixLabels
1.0
minPts=12
k=2
fu_flame
1.0
minPts=232
k=1
gionis_aggregation
1.0
minPts=113
k=1
veenman_r15
1.0
minPts=34
k=6
zahn_compound
1.0
minPts=239
k=1
synthetic_spirals
1.0
minPts=59
k=1
synthetic_cassini
1.0
minPts=42
k=9
twonorm_100d
1.0
minPts=95
k=1
twonorm_50d
1.0
minPts=10
k=1
synthetic_cuboid
1.0
minPts=10
k=5
bone_marrow
1.0
minPts=3
k=1