27 lines
691 B
Python
27 lines
691 B
Python
import os
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import xgboost as xgb
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from sklearn.datasets import make_classification
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from sklearn.metrics import roc_auc_score
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import sys
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def run_omp(output_path: str):
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X, y = make_classification(
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n_samples=200, n_features=32, n_classes=3, n_informative=8
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)
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Xy = xgb.DMatrix(X, y, nthread=16)
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booster = xgb.train(
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{"num_class": 3, "objective": "multi:softprob", "n_jobs": 16},
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Xy,
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num_boost_round=8,
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)
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score = booster.predict(Xy)
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auc = roc_auc_score(y, score, average="weighted", multi_class="ovr")
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with open(output_path, "w") as fd:
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fd.write(str(auc))
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if __name__ == "__main__":
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out = sys.argv[1]
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run_omp(out)
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