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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
0.995
I=2.1512512512512516
chang_pathbased
0.696
I=9.714914914914916
ppi_mips
0.993
I=4.173573573573573
chang_spiral
0.331
I=5.51881881881882
astral_40_strsim
0.991
I=8.824024024024025
astral_40_seqsim_beh
0.991
I=1.5632632632632633
fraenti_s3
0.067
I=7.1491491491491495
bone_marrow_fixLabels
0.361
I=1.126726726726727
fu_flame
0.536
I=3.7103103103103106
coli_state
0.391
I=9.5990990990991
coli_find
0.127
I=8.066766766766767
coli_need
0.387
I=4.333933933933935
coli_time
0.264
I=2.142342342342342
gionis_aggregation
0.217
I=7.362962962962963
veenman_r15
0.065
I=2.7926926926926927
zahn_compound
0.247
I=9.57237237237237
synthetic_spirals
0.498
I=9.955455455455455
synthetic_cassini
0.357
I=2.694694694694695
twonorm_100d
0.497
I=9.002202202202202
twonorm_50d
0.497
I=7.38078078078078
synthetic_cuboid
0.261
I=2.5165165165165164
astral1_161
0.852
I=8.61911911911912
tcga
0.554
I=9.233833833833835
bone_marrow
0.777
I=9.946546546546546
zachary
1.0
I=1.50980980980981