neg_log_loss_scorer = make_scorer(log_loss, greater_is_better=False, needs_proba=True) 它指定了greater_is_better=False,会给计算结果加上负号,为了给优化器用, 让这个分数越大越好,它的变量名字可以看出来neg_log_loss_scorer,是加了负号的logloss。如果希望就是原生的logloss,可以设置greater_is_better...
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This is a known problem forlog_loss, which was fixed by adding an argumentlabelsto that function:#4033 The problem above is,cross_val_scoreinvokes that function, but does not allow us to pass the labels. Ideally, cross_val_score should be able to infer the true labels from y=df1. ...
回归损失函数2 : HUber loss,Log Cosh Loss,以及 Quantile Loss 2019-12-17 15:27 − 均方误差(Mean Square Error,MSE)和平均绝对误差(Mean Absolute Error,MAE) 是回归中最常用的两个损失函数,但是其各有优缺点。为了避免MAE和MSE各自的优缺点,在Faster R-CNN和SSD中使用$\text{Smooth} L_1$损失函数...