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	0.993	method=average metric=euclidean k=27
chang_pathbased	0.799	method=ward metric=euclidean k=7
ppi_mips	0.284	method=single metric=euclidean k=950
chang_spiral	1.0	method=single metric=euclidean k=3
astral_40_strsim	0.848	method=average metric=euclidean k=85
astral_40_seqsim_beh	0.649	method=weighted metric=euclidean k=189
fraenti_s3	0.819	method=ward metric=euclidean k=11
bone_marrow_fixLabels	0.947	method=complete metric=euclidean k=3
fu_flame	0.956	method=single metric=euclidean k=12
coli_state	0.698	method=ward metric=euclidean k=1
coli_find	0.398	method=ward metric=euclidean k=10
coli_need	0.739	method=flexible metric=euclidean k=1
coli_time	0.597	method=average metric=euclidean k=3
gionis_aggregation	1.0	method=flexible metric=euclidean k=4
veenman_r15	0.995	method=single metric=euclidean k=8
zahn_compound	0.899	method=weighted metric=euclidean k=4
synthetic_spirals	1.0	method=weighted metric=euclidean k=5
synthetic_cassini	1.0	method=flexible metric=euclidean k=3
twonorm_100d	0.89	method=flexible metric=euclidean k=2
twonorm_50d	0.914	method=flexible metric=euclidean k=2
synthetic_cuboid	1.0	method=average metric=euclidean k=4
astral1_161	0.716	method=flexible metric=euclidean k=31
tcga	0.997	method=average metric=euclidean k=4
bone_marrow	0.895	method=single metric=euclidean k=3
zachary	1.0	method=ward metric=euclidean k=1