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	0.812	method=average metric=euclidean k=43
chang_pathbased	0.539	method=weighted metric=euclidean k=3
ppi_mips	0.052	method=average metric=euclidean k=983
chang_spiral	0.455	method=average metric=euclidean k=38
astral_40_strsim	0.172	method=single metric=euclidean k=316
astral_40_seqsim_beh	0.109	method=single metric=euclidean k=260
fraenti_s3	0.448	method=flexible metric=euclidean k=13
bone_marrow_fixLabels	0.338	method=complete metric=euclidean k=3
fu_flame	0.438	method=ward metric=euclidean k=6
coli_state	0.782	method=average metric=euclidean k=2
coli_find	0.813	method=weighted metric=euclidean k=2
coli_need	0.791	method=single metric=euclidean k=2
coli_time	0.833	method=complete metric=euclidean k=3
gionis_aggregation	0.526	method=average metric=euclidean k=3
veenman_r15	0.752	method=single metric=euclidean k=8
zahn_compound	0.55	method=weighted metric=euclidean k=4
synthetic_spirals	0.395	method=ward metric=euclidean k=57
synthetic_cassini	0.504	method=flexible metric=euclidean k=2
twonorm_100d	0.071	method=average metric=euclidean k=2
twonorm_50d	0.103	method=average metric=euclidean k=2
synthetic_cuboid	0.558	method=ward metric=euclidean k=5
astral1_161	0.111	method=ward metric=euclidean k=149
tcga	0.184	method=ward metric=euclidean k=2
bone_marrow	0.338	method=single metric=euclidean k=3
zachary	0.261	method=average metric=euclidean k=19