1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
|
import sys
from sklearn.datasets import make_classification
from sklearn.metrics import roc_auc_score
import xgboost as xgb
def run_omp(output_path: str):
X, y = make_classification(
n_samples=200, n_features=32, n_classes=3, n_informative=8
)
Xy = xgb.DMatrix(X, y, nthread=16)
booster = xgb.train(
{"num_class": 3, "objective": "multi:softprob", "n_jobs": 16},
Xy,
num_boost_round=8,
)
score = booster.predict(Xy)
auc = roc_auc_score(y, score, average="weighted", multi_class="ovr")
with open(output_path, "w") as fd:
fd.write(str(auc))
if __name__ == "__main__":
out = sys.argv[1]
run_omp(out)
|
