Dan Fitton continues a series on model evaluation with Azure Machine Learning:
The initial go-to metric for understanding a regression model is the R squared (or R2) value, also known as the coefficient of determination. R squared measures how well the model is fitted to the data – the goodness of fit. It indicates how much of the variation of y (the target) is explained by the variation in x (the features).
The measures are bog standard if you’ve worked with regressions before, and Dan does a good job explaining them.