# RMSE to accuracy

I have seen multiple questions and answers about this, but I haven't been able to understand, so, I'm gonna try to ask as simple as possible. I have built several models to forecast future value of a variable. When I test the model (on out of training data) I have received the RMSE obtained by each one.

Example:

RMSE: 0.05, Min value of dataset: 1, Max value of dataset: 2


How can I calculate the accuracy of the model? Sorry if the question is duplicated, thanks in advance.

• Is this a classification or regression problem? – Dave Sep 8 '20 at 23:22
• Regression problem – David Díaz Sep 8 '20 at 23:23
• Then what do you mean by “accuracy”? – Dave Sep 8 '20 at 23:23
• The effectiveness (in percentage), is it wrong? – David Díaz Sep 8 '20 at 23:26

Answering with a question: you would like to calculate "percentage" of what exactly? If you want to have a unitless measure, you can take a look at MAPE (see ), or $$R^2$$ (see ), but as you can learn from What are the shortcomings of the Mean Absolute Percentage Error (MAPE)? and Is $R^2$ useful or dangerous?, both have their shortcomings. Moreover, accuracy is a far from perfect measure of model performance, and there are many issues with it, so for classification problems this is often not the best choice for a metric as well.