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Use auc score to unify the intermediate and objective values #272

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merged 2 commits into from
Jul 29, 2024
Merged

Use auc score to unify the intermediate and objective values #272

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e0a698a
replace accuracy with auc in the best score attribute
nzw0301 Jul 13, 2024
a231306
Use numpy function to compute AUC score
nzw0301 Jul 24, 2024
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5 changes: 1 addition & 4 deletions lightgbm/lightgbm_integration.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,6 @@

"""

import numpy as np
import optuna

import lightgbm as lgb
Expand Down Expand Up @@ -46,9 +45,7 @@ def objective(trial):
gbm = lgb.train(param, dtrain, valid_sets=[dvalid], callbacks=[pruning_callback])

preds = gbm.predict(valid_x)
pred_labels = np.rint(preds)
accuracy = sklearn.metrics.accuracy_score(valid_y, pred_labels)
return accuracy
return sklearn.metrics.roc_auc_score(valid_y, preds)


if __name__ == "__main__":
Expand Down