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. 2014 Apr 17;14:82. doi: 10.1186/1471-2148-14-82

Table 2.

AICc and BIC scores of the best partitioning scheme found by different algorithms on each dataset

 
AICc
BIC
Dataset Greedy
Relaxed clustering
Strict clustering
Greedy
Relaxed clustering
Strict clustering
(AICc) (ΔAICc) (ΔAICc) (BIC) (ΔBIC) (ΔBIC)
Ward_2010
103258
-34
-61
104877
-294
-606
Wainwright_2012
473537
-7
-59
477322
-73
-663
Pyron_2011
154838
-42
-173
156039
-177
-383
Li_2008
252583
-6
-242
254327
-183
-769
Leavitt_2013
424129
-216
-757
426143
-837
-3176
Kaffenberger_2011
120020
-6
-75
121452
-62
-150
Irisarri_2012
214655
-41
-187
216209
-152
-1151
Hackett_2008
1830824
-356
-1442
1837230
-964
-6362
Fong_2012
276517
-254
-1508
278400
-900
-2129
Endicott_2008 66966 -90 -479 70139 -455 -752

The greedy algorithm performed best in all cases, as expected, and the AICc/BIC score is shown for each run with that algorithm. The relaxed clustering algorithm typically performed almost as well as the greedy algorithm, and always performed better than the strict clustering algorithm. ΔAICc or ΔBIC scores are shown for the clustering algorithms, and represent the difference in AICc or BIC score from the greedy algorithm.