模型auc #82
Description
看着模型的auc 似乎挺低的，只有0.64左右，请问这个符合预期吗？
y label is: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
y pred is: [0.05798095 0.03533146 0.01641405 0.03143436 0.03862092 0.03267911
0.05392143 0.02281025 0.01579049 0.01842922]
y label is: [0, 0, 0, 0, 0, 0, 0, 0, 1, 0]
[22] train-result=0.6407, valid-result=0.6343 [9.4 s]
y pred is: [0.03750926 0.01880527 0.05569485 0.07267779 0.05398676 0.01429421
0.04875255 0.0505054 0.04599738 0.01642129]
y label is: [0, 0, 0, 0, 0, 0, 0, 0, 1, 0]
y pred is: [0.05662587 0.03662628 0.0164277 0.03011197 0.03908774 0.03087404
0.05263913 0.02288574 0.01674244 0.01785788]
y label is: [0, 0, 0, 0, 0, 0, 0, 0, 1, 0]
[23] train-result=0.6407, valid-result=0.6337 [9.5 s]
y pred is: [0.03384528 0.02579725 0.0337351 0.01474965 0.01980248 0.08577338
0.03570223 0.02154443 0.01600081 0.06123042]
y label is: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
y pred is: [0.05355939 0.03428313 0.01536882 0.02870828 0.03626341 0.02892247
0.04818174 0.02135336 0.01569992 0.01592934]
y label is: [0, 0, 0, 0, 0, 0, 0, 0, 1, 0]
[24] train-result=0.6408, valid-result=0.6339 [9.4 s]
y pred is: [0.04230124 0.01995093 0.02749962 0.03038487 0.0186753 0.05878732
0.0560405 0.04908311 0.02376211 0.04664466]
y label is: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
y pred is: [0.06111899 0.03893104 0.01835153 0.03404051 0.0419451 0.03517583
0.05543426 0.02484268 0.01772082 0.01910195]
y label is: [0, 0, 0, 0, 0, 0, 0, 0, 1, 0]
[25] train-result=0.6409, valid-result=0.6341 [10.0 s]
y pred is: [0.01998511 0.01615599 0.02129778 0.05111638 0.02586061 0.02680564
0.03819406 0.02972624 0.02138367 0.0199841 ]
y label is: [0, 0, 0, 0, 0, 0, 1, 0, 0, 0]
y pred is: [0.05024683 0.03149936 0.01417857 0.02725089 0.03441039 0.02746817
0.04541245 0.01985681 0.0140177 0.01490432]
y label is: [0, 0, 0, 0, 0, 0, 0, 0, 1, 0]
[26] train-result=0.6408, valid-result=0.6341 [10.8 s]
y pred is: [0.03094813 0.11031216 0.08970305 0.01912943 0.02922311 0.04867047
0.04063419 0.03129154 0.06203148 0.01524448]
y label is: [0, 0, 0, 1, 0, 0, 0, 0, 0, 0]
y pred is: [0.05720276 0.0351117 0.01653779 0.03097847 0.03837138 0.03197479
0.05335689 0.02237967 0.01642597 0.017708 ]
y label is: [0, 0, 0, 0, 0, 0, 0, 0, 1, 0]
[27] train-result=0.6410, valid-result=0.6341 [10.9 s]
y pred is: [0.05627459 0.02199188 0.0286133 0.0340426 0.0272944 0.02497771
0.06165919 0.02150139 0.02828825 0.0466111 ]
y label is: [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
y pred is: [0.05718008 0.03378567 0.01614183 0.03007659 0.03684855 0.03177223
0.0514642 0.02198145 0.01576105 0.01745546]
y label is: [0, 0, 0, 0, 0, 0, 0, 0, 1, 0]
[28] train-result=0.6409, valid-result=0.6345 [10.0 s]
y pred is: [0.0285311 0.03491145 0.05508521 0.02977163 0.0397478 0.0387173
0.04933062 0.01876742 0.05117655 0.03493056]