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	0.987	method=average metric=euclidean k=27
chang_pathbased	0.807	method=weighted metric=euclidean k=7
ppi_mips	0.33	method=weighted metric=euclidean k=957
chang_spiral	1.0	method=ward metric=euclidean k=3
astral_40_strsim	0.851	method=average metric=euclidean k=85
astral_40_seqsim_beh	0.714	method=weighted metric=euclidean k=275
fraenti_s3	0.822	method=ward metric=euclidean k=11
bone_marrow_fixLabels	0.948	method=complete metric=euclidean k=3
fu_flame	0.972	method=complete metric=euclidean k=18
coli_state	0.546	method=single metric=euclidean k=7
coli_find	0.241	method=flexible metric=euclidean k=13
coli_need	0.55	method=average metric=euclidean k=1
coli_time	0.404	method=ward metric=euclidean k=9
gionis_aggregation	1.0	method=flexible metric=euclidean k=4
veenman_r15	0.995	method=single metric=euclidean k=8
zahn_compound	0.878	method=complete metric=euclidean k=56
synthetic_spirals	1.0	method=flexible metric=euclidean k=2
synthetic_cassini	1.0	method=flexible metric=euclidean k=3
twonorm_100d	0.89	method=average metric=euclidean k=3
twonorm_50d	0.915	method=single metric=euclidean k=4
synthetic_cuboid	1.0	method=single metric=euclidean k=4
astral1_161	0.764	method=average metric=euclidean k=50
tcga	0.998	method=average metric=euclidean k=4
bone_marrow	0.896	method=single metric=euclidean k=3
zachary	1.0	method=average metric=euclidean k=2