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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=42
k=183
chang_spiral
1.0
minPts=3
k=153
fraenti_s3
1.0
minPts=1191
k=5000
bone_marrow_fixLabels
1.0
minPts=23
k=38
fu_flame
1.0
minPts=80
k=232
gionis_aggregation
1.0
minPts=132
k=368
veenman_r15
1.0
minPts=10
k=93
zahn_compound
1.0
minPts=32
k=181
synthetic_spirals
1.0
minPts=12
k=22
synthetic_cassini
1.0
minPts=190
k=238
twonorm_100d
1.0
minPts=162
k=200
twonorm_50d
1.0
minPts=54
k=200
synthetic_cuboid
1.0
minPts=7
k=14
bone_marrow
1.0
minPts=6
k=30