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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=144
chang_pathbased
1.0
k=191
ppi_mips
1.0
k=1050
chang_spiral
1.0
k=132
astral_40_strsim
1.0
k=873
astral_40_seqsim_beh
1.0
k=823
fraenti_s3
0.999
k=217
bone_marrow_fixLabels
1.0
k=24
fu_flame
1.0
k=91
coli_state
1.0
k=183
coli_find
1.0
k=414
coli_need
1.0
k=102
coli_time
1.0
k=507
gionis_aggregation
1.0
k=751
veenman_r15
1.0
k=592
zahn_compound
1.0
k=284
synthetic_spirals
1.0
k=110
synthetic_cassini
1.0
k=35
twonorm_100d
1.0
k=195
twonorm_50d
1.0
k=196
synthetic_cuboid
1.0
k=216
astral1_161
1.0
k=368
tcga
1.0
k=123
bone_marrow
1.0
k=34
zachary
1.0
k=12