Clust
Eval
clustering evaluation framework
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k-Means
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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
0.798
k=7
nstart=10
chang_spiral
0.7
k=30
nstart=10
fraenti_s3
0.965
k=47
nstart=10
bone_marrow_fixLabels
0.959
k=8
nstart=10
fu_flame
0.727
k=2
nstart=10
gionis_aggregation
0.933
k=6
nstart=10
veenman_r15
0.995
k=18
nstart=10
zahn_compound
0.889
k=5
nstart=10
synthetic_spirals
0.518
k=12
nstart=10
synthetic_cassini
0.84
k=5
nstart=10
twonorm_100d
0.932
k=2
nstart=10
twonorm_50d
0.951
k=3
nstart=10
synthetic_cuboid
1.0
k=5
nstart=10
bone_marrow
0.9
k=3
nstart=10