2017年2月8日 · RRMSE can also be used to hide inaccuracy. If you're comparing different techniques of measuring large magnitude items, say distances of 10,000 m, one may be established and very accurate, measuring within .05 m accuracy, while the proposed new technique is much less precise, measuring within 200 m accuracy.

2021年2月4日 · In a few days I start in a datathon in which they have tell us the formula of RRMSE is (1), but I tried to search some implementation, and while searching for it I saw in CrossValidated a person saying that rRMSE is RMSE/mean, then I founded a github code in R (Fgmutils) with the same formula, and the same one in a python package (spotpy).

2019年6月15日 · Another reference for using RRMSE could be found here and the last form is known as r RMSE as well as shown here Basically the same approach is used in MAPE to express error either relatively or in form of percentage as the last form.

2024年11月27日 · I have been wondering for quite some time about the expression of the relative root mean squared error, RRMSE, as it is been considered in the literature.

Yes, it is called the coefficient of variation. See this question for some discussion about this parameter, or read the Wikipedia entry.

2013年4月17日 · I think you have two different types of questions there. One thing is what you ask in the title: "What are good RMSE values?" and another thing is how to compare models with different datasets using RMSE. For the first, i.e., the question in the title, it is important to recall that RMSE has the same unit as the dependent variable (DV). It means that there is no …

2021年12月1日 · I have a weekly times series for which I would like to find the best fit model. So far I've tried arima, Harmonic regression with arima error, neural network and in the end I would like to decide w...

2015年3月18日 · the reason this has been confirmed as the 'general' case is that the number of parameters K is assumed to be equal to 0. Regardless, this is not always the case, especially in the case of linear regression as it might lead to misleading results. That is why, for example, MATLAB's implementation counts the number of parameters and takes them off the total …

The response values in my data set (100 data points) are all positive integers (should not be either negative or zero values). I have developed two statistical models: Linear Regression (LR) and K

2019年1月22日 · Try plotting your data and looking at the distributions of Set i and Set j. There is no single answer to your question "is the similarity between these lists high or low?"; that can only be addressed in terms of how you wish to use these data. Although you have a wide range of values in both Set i and Set j from nearly 0 to 2 or more, about 90% of values in both sets are …