如何使用numpy在python中计算RMSPE [英] How to calculate RMSPE in python using numpy

问题描述

我正在使用 Rossmann数据集进行多变量预测.现在，我需要使用RMSPE指标来评估我的模型.我在此处看到了相关公式.但是我不确定如何使用numpy有效地实现这一点.任何帮助深表感谢.

I am doing a multivariate forecasting using the Rossmann dataset. I now need to use the RMSPE metric to evaluate my model. I saw the relevant formula here. But I am not sure how to efficiently implement this using numpy. Any help is much appreciated.

推荐答案

您可以利用numpy的矢量化功能来实现这样的错误度量.以下函数可用于计算RMSPE:

You can take advantage of numpy's vectorisation capability for an error metric like this. The following function can be used to compute RMSPE:

def rmse(y_true, y_pred):
    '''
    Compute Root Mean Square Percentage Error between two arrays.
    '''
    loss = np.sqrt(np.mean(np.square(((y_true - y_pred) / y_true)), axis=0))

    return loss

(对于向量之间的错误，axis=0明确指出该错误是按行计算的，并返回向量.这不是必需的，因为这是np.mean的默认行为.)

(For the error between vectors, axis=0 makes it explicit that the error is computed row-wise, returning a vector. It isn't required, as this is the default behaviour for np.mean.)

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