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=53 membexp=2.0
chang_pathbased	1.0	k=112 membexp=5.0
ppi_mips	1.0	k=373 membexp=1.1
chang_spiral	1.0	k=115 membexp=5.0
astral_40_strsim	1.0	k=452 membexp=2.0
astral_40_seqsim_beh	1.0	k=392 membexp=2.0
fraenti_s3	1.0	k=543 membexp=1.1
bone_marrow_fixLabels	0.982	k=7 membexp=2.0
fu_flame	1.0	k=108 membexp=5.0
coli_state	1.0	k=190 membexp=5.0
coli_find	1.0	k=161 membexp=1.1
coli_need	1.0	k=105 membexp=5.0
coli_time	1.0	k=75 membexp=1.1
gionis_aggregation	1.0	k=262 membexp=1.1
veenman_r15	1.0	k=151 membexp=2.0
zahn_compound	1.0	k=156 membexp=1.1
synthetic_spirals	1.0	k=66 membexp=1.1
synthetic_cassini	1.0	k=16 membexp=5.0
twonorm_100d	1.0	k=28 membexp=7.33
twonorm_50d	1.0	k=87 membexp=7.33
synthetic_cuboid	1.0	k=31 membexp=2.0
astral1_161	1.0	k=208 membexp=2.0
tcga	1.0	k=113 membexp=1.1
bone_marrow	0.993	k=16 membexp=1.1
zachary	1.0	k=2 membexp=2.0