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	1.0	k=68 membexp=1.1
chang_pathbased	1.0	k=154 membexp=5.0
ppi_mips	1.0	k=495 membexp=2.0
chang_spiral	1.0	k=144 membexp=1.1
astral_40_strsim	1.0	k=266 membexp=1.1
astral_40_seqsim_beh	1.0	k=36 membexp=2.0
fraenti_s3	1.0	k=363 membexp=5.0
bone_marrow_fixLabels	0.982	k=7 membexp=2.0
fu_flame	1.0	k=109 membexp=1.1
coli_state	1.0	k=75 membexp=2.0
coli_find	1.0	k=182 membexp=1.1
coli_need	1.0	k=44 membexp=1.1
coli_time	1.0	k=242 membexp=5.0
gionis_aggregation	1.0	k=224 membexp=1.1
veenman_r15	1.0	k=270 membexp=5.0
zahn_compound	1.0	k=74 membexp=2.0
synthetic_spirals	1.0	k=121 membexp=5.0
synthetic_cassini	1.0	k=60 membexp=5.0
twonorm_100d	1.0	k=200 membexp=8.516666666666667
twonorm_50d	1.0	k=74 membexp=10.0
synthetic_cuboid	1.0	k=118 membexp=5.0
astral1_161	1.0	k=236 membexp=1.1
tcga	1.0	k=94 membexp=5.0
bone_marrow	0.993	k=16 membexp=1.1
zachary	1.0	k=2 membexp=2.0