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clustering evaluation framework
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Markov Clustering
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Best Parameters
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General
Best Qualities
Best Parameters
Hints:
Which parameter sets lead to the optimal clustering quality?
Please choose a clustering quality measure:
Davies Bouldin Index (R)
Dunn Index (R)
F1-Score
F2-Score
False Discovery Rate
False Positive Rate
Fowlkes Mallows Index (R)
Jaccard Index (R)
Rand Index
Rand Index (R)
Sensitivity
Silhouette Value (R)
Specificity
V-Measure
Dataset
Best quality
Parameter set
brown
0.997
I=9.75055055055055
chang_pathbased
0.648
I=9.706006006006005
ppi_mips
0.993
I=5.260460460460461
chang_spiral
0.0
I=3.184684684684685
astral_40_strsim
0.999
I=9.884184184184184
astral_40_seqsim_beh
0.999
I=9.857457457457457
fraenti_s3
0.0
I=8.227127127127126
bone_marrow_fixLabels
0.0
I=1.1356356356356356
fu_flame
0.0
I=4.725925925925926
coli_state
0.0
I=9.821821821821821
coli_find
0.0
I=7.175875875875876
coli_need
0.0
I=4.761561561561562
coli_time
0.0
I=1.1
gionis_aggregation
0.0
I=4.717017017017017
veenman_r15
0.0
I=3.157957957957958
zahn_compound
0.0
I=5.465365365365365
synthetic_spirals
0.5
I=9.706006006006005
synthetic_cassini
0.0
I=7.095695695695696
twonorm_100d
0.0
I=3.567767767767768
twonorm_50d
0.0
I=2.400700700700701
synthetic_cuboid
0.0
I=2.2581581581581585
astral1_161
0.964
I=9.955455455455455
tcga
0.0
I=9.305105105105104
bone_marrow
0.659
I=10.0
zachary
1.0
I=2.65015015015015