Machine Learning, Linear Regression, Data Science, Artificial Intelligence.
authorship. Model Bias vs variance Let’s define two concepts before introducing regularization: Model variance: It is the spread, or variability, of the model prediction for a given data point. Model bias: The difference between the expectation of the model prediction and the real target. As the