Table 4 Precision comparison results on ten datasets averaged over 1000 runs.
From: A potential energy and mutual information based link prediction approach for bipartite networks
Dataset | ML | EN | SWN | CL | CM | IC | C2O | Mal | GPC | Drug |
|---|---|---|---|---|---|---|---|---|---|---|
PA | .153 | .023 | .122 | .110 | .157 | .036 | .871 | .022 | .081 | .313 |
CN | .141 | .370 | .141 | .210 | .202 | .230 | .871 | .192 | .310 | .610 |
JC | .001 | .031 | .021 | .042 | .036 | .021 | .601 | .250 | .012 | .383 |
CAR | .177 | .507 | .188 | .189 | .202 | .432 | .871 | .191 | .332 | .601 |
CJC | .184 | .496 | .188 | .217 | .231 | .494 | .871 | .232 | .361 | .191 |
CAA | .181 | .502 | .122 | .662 | .621 | .531 | .870 | .191 | .320 | .591 |
CRA | .181 | .651 | .210 | .612 | .631 | .560 | .880 | .251 | .373 | .631 |
BPR | .181 | .501 | .162 | .620 | .641 | .442 | .931 | .253 | .271 | .680 |
CS | .120 | .330 | .163 | .165 | .455 | .349 | .661 | .142 | .201 | .491 |
PLP | .191 | .491 | .410 | .210 | .620 | .612 | .631 | .221 | .283 | .301 |
NMF | .001 | .001 | .031 | .022 | .031 | .011 | .001 | .001 | .012 | .021 |
PMIL | .210 | .661 | .441 | .205 | .651 | .581 | .601 | .261 | .401 | .310 |
