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	0.872	k=21 membexp=2.0
chang_pathbased	0.829	k=44 membexp=1.1
ppi_mips	0.997	k=528 membexp=1.1
chang_spiral	0.705	k=26 membexp=5.0
astral_40_strsim	0.993	k=219 membexp=2.0
astral_40_seqsim_beh	0.989	k=505 membexp=5.0
fraenti_s3	0.964	k=17 membexp=2.0
bone_marrow_fixLabels	0.959	k=2 membexp=2.0
fu_flame	0.773	k=4 membexp=5.0
coli_state	0.614	k=26 membexp=5.0
coli_find	0.873	k=144 membexp=2.0
coli_need	0.613	k=44 membexp=1.1
coli_time	0.736	k=247 membexp=5.0
gionis_aggregation	0.932	k=4 membexp=5.0
veenman_r15	0.998	k=18 membexp=2.0
zahn_compound	0.909	k=17 membexp=5.0
synthetic_spirals	0.515	k=22 membexp=1.1
synthetic_cassini	0.951	k=3 membexp=1.1
twonorm_100d	0.819	k=2 membexp=1.3966666666666667
twonorm_50d	0.951	k=2 membexp=1.99
synthetic_cuboid	1.0	k=6 membexp=1.1
astral1_161	0.862	k=46 membexp=2.0
tcga	0.908	k=2 membexp=5.0
bone_marrow	0.9	k=3 membexp=1.1
zachary	1.0	k=2 membexp=2.0