Clust
Eval
clustering evaluation framework
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Location:
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brown
»
Best Qualities
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General
Statistics
Best Qualities
Best Parameters
All Clusterings
Hints:
How well do clustering methods perform on 'brown'?
Program
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
CLARA
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Self Organizing Maps
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Spectral Clustering
0.539
NaN
0.656
0.651
0.0
0.0
0.653
0.451
0.858
0.858
0.965
0.47
1.0
0.795
clusterdp
0.482
2.95
0.975
0.979
0.002
0.0
0.997
0.995
0.999
0.999
1.0
0.769
1.0
0.986
HDBSCAN
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AGNES
0.1
NaN
0.987
0.993
0.0
0.0
NaN
0.999
1.0
1.0
1.0
NaN
1.0
0.994
c-Means
0.539
NaN
0.78
0.75
0.0
0.0
NaN
0.644
0.899
0.899
0.965
0.562
1.0
0.828
k-Medoids (PAM)
0.112
NaN
0.912
0.888
0.0
0.0
0.953
0.909
0.979
0.979
0.999
0.764
1.0
0.938
DIANA
0.123
NaN
0.991
0.995
0.0
0.0
NaN
0.999
1.0
1.0
1.0
NaN
1.0
0.996
DBSCAN
0.405
NaN
0.68
0.593
0.0
0.0
0.481
0.237
0.832
0.832
1.0
NaN
1.0
0.759
Hierarchical Clustering
0.077
NaN
0.987
0.993
0.0
0.0
NaN
0.999
1.0
1.0
1.0
NaN
1.0
0.994
fanny
0.484
NaN
0.767
0.759
0.003
0.0
NaN
0.525
0.872
0.872
1.0
NaN
1.0
0.79
k-Means
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DensityCut
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clusterONE
0.558
2.14
0.942
0.948
0.039
0.011
0.976
0.953
0.99
0.99
1.0
NaN
0.989
0.961
Affinity Propagation
0.5
1.777
0.91
0.917
0.014
0.004
0.984
0.969
0.993
0.993
0.988
0.705
0.996
0.945
Markov Clustering
0.49
2.769
0.923
0.948
0.012
0.003
0.988
0.976
0.995
0.995
1.0
0.772
0.997
0.955
Transitivity Clustering
0.025
NaN
0.986
0.987
0.0
0.0
NaN
0.996
0.999
0.999
1.0
NaN
1.0
0.991
MCODE
0.499
1.94
0.931
0.952
0.019
0.005
0.99
0.981
0.996
0.996
1.0
0.75
0.995
0.959