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clustering evaluation framework
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k-Medoids (PAM)
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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
brown
1.0
k=225
chang_pathbased
1.0
k=175
ppi_mips
1.0
k=1071
chang_spiral
1.0
k=70
astral_40_strsim
1.0
k=399
astral_40_seqsim_beh
1.0
k=741
fraenti_s3
0.999
k=217
bone_marrow_fixLabels
1.0
k=35
fu_flame
1.0
k=191
coli_state
1.0
k=172
coli_find
1.0
k=419
coli_need
1.0
k=102
coli_time
1.0
k=510
gionis_aggregation
1.0
k=508
veenman_r15
1.0
k=501
zahn_compound
1.0
k=339
synthetic_spirals
1.0
k=67
synthetic_cassini
1.0
k=92
twonorm_100d
1.0
k=199
twonorm_50d
1.0
k=181
synthetic_cuboid
1.0
k=211
astral1_161
1.0
k=490
tcga
1.0
k=98
bone_marrow
1.0
k=30
zachary
1.0
k=9