Data Science, Regularization, Machine Learning, Editors Pick, Hands On Tutorials.
It shows how much of the variability in the target is explained by the features[1]. For instance, if you’re fitting a linear model to the data but there’s no linear relationship between target and features, R-squared is going tot be very close to zero. Bias and variance are metrics that help