RMSLE惩罚欠预测大于过预测。我是看bike sharing demand问题见到这个指标的，结合实际考虑某些情况下会存在...
mean_squared_logarithmic_error(y_true, y_pred) assert loss.shape == (2,) y_true = np.maximum(y_true, 1e-7) y_pred = np.maximum(y_pred, 1e-7) assert np.allclose( loss.numpy(), np.mean( np.square(np.log(y_true + 1.) - np.log(y_pred + 1.)), axis=-1))...
为解决此问题，考虑使用对数RMSE（logarithmic RMSE）。先取对数操作，可以稍微缓解大值误差对整体评估的影响。RMSE在预测值分布固定时，评估结果较为合理。然而，对数转换后的RMSE同样存在适用范围限制，其效果依赖于数据特性。
RMSE会被明显拉大，这时候就需要先对数据log下，再求RMSE，这个过程就是RMSLE。对低估值（under-predict...
Root Mean Squared Logarithmic Error Lossytrue
The root mean squared logarithmic error (RMSLE). RMSLE=1n∑i=1n(log(yiˆ+1)−log(yi+1))2 6.6.4Mean absolute percent error The mean absolute percent error (MAPE) is theamount of the accuracy of a prediction. It measures the size of the error (Fig. 6.5;Table 6.1). ...
Sharp bounds for the Neuman-Sandor mean in terms of generalized logarithmic mean We also improve on the mean squared error upper bound for answering counting queries on a database of size n n by Blum, Ligett, and Roth, and ... 褚玉明,李永民,龙波涌 被引量: 81发表: 2012年 加载更多来源...
The log mean temperature difference formula is: ΔTlm=ΔT1−ΔT2lnΔT1ΔT2ΔTlm=lnΔT2ΔT1ΔT1−ΔT2 where: ΔT1ΔT1 and ΔT2ΔT2 –Temperature differences for fluids at the inlet and outlet of the heat exchanger; and ΔTlmΔTlm –Logarithmic mean temperature difference. ...
We account for diminishing returns by using the logged values of all continuous, independent variables, resulting in a semilogarithmic model (Leeflang et al., 2016).12 Endogeneity. Financially successful firms could be able to invest in market share-increasing activities such as advertising or new ...
求助：用xgboost的eval_metric只有rmse，没有rmsle。怎么自定义？