PMC full text:
Mach Learn. Author manuscript; available in PMC 2018 Feb 16.
Published in final edited form as:
Table 3
Performance comparisons between different classification methods on 1000 simulated training spaces. The second column gives the average over all training spaces of the 11-point average precision for each of the different methods. The counts listed in a given row and column give the number of training spaces on which the performance of the method listed on that row outperformed/equaled/fell below the method listed at the top of that column.
11-pap | PAV-Ada | LinAda | StmpAda | Bayes’ | |
---|---|---|---|---|---|
Ideal | 0.7721 | 962/38/0 | 993/7/0 | 990/10/0 | 993/7/0 |
PavAda | 0.7321 | 949/41/10 | 885/37/78 | 954/44/2 | |
LinAda | 0.7053 | 10/41/949 | 220/534/246 | 67/901/32 | |
StmpAda | 0.7047 | 78/37/885 | 246/534/220 | 284/494/222 | |
Bayes’ | 0.7042 | 2/44/954 | 32/901/67 | 222/494/284 | |
Random | 0.5039 | 0/0/1000 | 0/0/1000 | 0/0/1000 | 0/0/1000 |