Table 3.
Model Performance
| NLSVR | PCR | LNSVR | ANN | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| NFS | DEG | LIM | NFS | DEG | LIM | NFS | DEG | LIM | NFS | DEG | LIM | |
| BLM | .207 | .202 | .202 | .239 | .208 | .208 | .151 | .1 | .209 | .147 | .17 | .21 |
| BTZ | .38 | .404 | .365 | .422 | .399 | .354 | .332 | .326 | .232 | −.009 | .299 | .24 |
| CIS | .05 | .08 | N/A | −.009 | .047 | N/A | .03 | .079 | N/A | −.066 | .034 | N/A |
| CYT | .313 | .32 | .279 | .32 | .281 | .256 | .337 | .291 | .269 | .226 | .266 | .291 |
| DTX | .422 | .44 | .408 | .367 | .409 | .382 | .357 | .319 | .359 | .185 | .318 | .207 |
| DOX | .273 | .27 | .117 | .243 | .285 | .106 | .27 | .226 | .103 | .115 | .173 | .096 |
| ETP | .289 | .302 | .294 | .248 | .291 | .263 | .238 | .219 | .273 | .209 | .195 | .246 |
| GEM | .143 | .139 | .166 | .153 | .117 | .143 | .07 | .063 | .165 | .131 | .119 | .134 |
| MTX | .461 | .455 | .462 | .431 | .435 | .433 | .417 | .388 | .338 | .411 | .391 | .322 |
| MMC | .237 | .302 | .244 | .264 | .269 | .25 | .27 | .224 | .239 | .203 | .153 | .248 |
| PTX | .32 | .27 | .198 | .287 | .282 | .159 | .233 | .170 | .191 | −.106 | .211 | .177 |
| VBL | .44 | .403 | .399 | .408 | .398 | .37 | .398 | .339 | .371 | .112 | .302 | .363 |
| VOR | .509 | .495 | .486 | .5 | .487 | .439 | .484 | .471 | .404 | .445 | .42 | .42 |
| SN-38 | .383 | .417 | .409 | .379 | .391 | .443 | .397 | .404 | .429 | .01 | .327 | .402 |
| 5-FU | .463 | .464 | .40 | .455 | .484 | .354 | .451 | .438 | .337 | .309 | .409 | .365 |
| AVG | .326 | .331 | .316 | .314 | .319 | .297 | .285 | .27 | .28 | .144 | .252 | 0.266 |
Average spearman correlations across six different testing sets for all regression and feature selection methods. This data is graphically displayed in Fig. 3