2

In this blog, which explains the meaning of bias and variance in machine learning, there's a line under the heading "Bias-Variance Trade-Off" which says:

Parametric or linear machine learning algorithms often have a high bias but a low variance.

I know that there's an "often" in the first sentence, but how can it be true?

If a linear ML algorithm has high bias how can we expect it to have low variance?

3I am afraid your definitions of bias and variance are wrong. These quantities can only be calculated if the true underlying data generation process is known. Which is never the case in practice. – Michael M – 2018-12-15T07:11:57.283

1Well, you are right in some sense. From a statistical point of view, there is a mathematical formula for both bias and variance, related to the expectation of the difference between the estimates and the true values... But in the ML field, is quite often to talk about the bias and the variance in that way – ignatius – 2018-12-17T08:37:35.047