|
Exp
|
Method
|
P
|
r
|
F
|
signif
|
% alt
|
|---|
|
A
|
CRF noalt, nom and word
|
0.9255
|
0.8885
|
0.9066
|
1-19, C-F
|
13.62
|
|
B
|
BDT nom and word
|
0.9221
|
0.8885
|
0.9050
|
1-19, C-F
|
25.67
|
|
C
|
BDT nom and word, top 10 teams
|
0.9118
|
0.8768
|
0.8940
|
1-19, E, F
|
23.37
|
|
D
|
BDT nom only
|
0.9092
|
0.8773
|
0.8929
|
1-19, E, F
|
25.42
|
|
E
|
BDT noalt, nom and word
|
0.9242
|
0.8165
|
0.8670
|
7-19, F
|
9.58
|
|
F
|
BDT word only
|
0.7165
|
0.6187
|
0.6640
|
18-19
|
37.07
|
- The precision, recall, and F score of machine learning experiments to learn gene mentions using the data extracted from all submitted runs as features. Method column: BDT, boosted decision trees; CRF, conditional random fields; nom, all nomination features; word, words of candidate; noalt, alternate gene data not used. The column signif indicates the ranks of runs for which there was a significant difference, and the letters indicate the machine learning experiments for which there was a significant difference. The column % alt gives the percentage of alternate gene mentions among the resulting true positives.
