问LightGBM二值分类模型:预测分数到类概率
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Stack Overflow用户

提问于 2022-10-05 19:58:48

回答 2查看 194关注 0票数 -1

我在一个分类(二进制)数据集上训练一个LGBM模型。

import lightgbm as lgb
def lgb_train(train_set, features, train_label_col, sample_weight_col=None, hyp = hyp):
    train_data = lgb.Dataset(data=train_set[features], label=train_set[train_label_col],)
    model = lgb.train(
        train_set=train_data,
        params=hyp,
        num_boost_round=hyp['num_boost_round'],
    )        
    return model

preds = np.array(model.predict(test_features))

现在，问题是:当我调用predict函数时，我得到一个分数[0.00012, 0.0035, 0.0000048]，我如何计算每个类的概率？

python