ClustEval | Which parameter sets lead to the optimal clustering quality?

ClustEval clustering evaluation framework

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Which parameter sets lead to the optimal clustering quality?

Please choose a clustering quality measure:

Dataset	Best quality	Parameter set
brown	0.999	method=complete metric=euclidean k=25
chang_pathbased	0.605	method=single metric=euclidean k=11
ppi_mips	0.076	method=average metric=euclidean k=957
chang_spiral	1.0	method=weighted metric=euclidean k=3
astral_40_strsim	0.58	method=weighted metric=euclidean k=243
astral_40_seqsim_beh	0.418	method=weighted metric=euclidean k=275
fraenti_s3	0.537	method=ward metric=euclidean k=11
bone_marrow_fixLabels	0.807	method=complete metric=euclidean k=3
fu_flame	0.918	method=weighted metric=euclidean k=10
coli_state	0.405	method=flexible metric=euclidean k=6
coli_find	0.13	method=single metric=euclidean k=15
coli_need	0.387	method=flexible metric=euclidean k=1
coli_time	0.264	method=weighted metric=euclidean k=1
gionis_aggregation	1.0	method=flexible metric=euclidean k=4
veenman_r15	0.98	method=single metric=euclidean k=8
zahn_compound	0.92	method=complete metric=euclidean k=56
synthetic_spirals	1.0	method=weighted metric=euclidean k=5
synthetic_cassini	1.0	method=average metric=euclidean k=3
twonorm_100d	0.671	method=ward metric=euclidean k=2
twonorm_50d	0.731	method=weighted metric=euclidean k=2
synthetic_cuboid	1.0	method=single metric=euclidean k=3
astral1_161	0.505	method=weighted metric=euclidean k=81
tcga	0.991	method=single metric=euclidean k=4
bone_marrow	0.694	method=ward metric=euclidean k=3
zachary	1.0	method=flexible metric=euclidean k=1