Clust
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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
1.0
k=262
nstart=10
chang_spiral
1.0
k=303
nstart=10
fraenti_s3
1.0
k=4978
nstart=10
bone_marrow_fixLabels
0.996
k=21
nstart=10
fu_flame
1.0
k=107
nstart=10
gionis_aggregation
1.0
k=324
nstart=10
veenman_r15
1.0
k=468
nstart=10
zahn_compound
1.0
k=368
nstart=10
synthetic_spirals
1.0
k=231
nstart=10
synthetic_cassini
1.0
k=73
nstart=10
twonorm_100d
1.0
k=198
nstart=10
twonorm_50d
1.0
k=188
nstart=10
synthetic_cuboid
1.0
k=91
nstart=10
bone_marrow
1.0
k=33
nstart=10