Machine Learning, Artificial Intelligence, Data Science, Heartbreak, Linear Regression.
is by reducing the magnitudes of the coefficients which can be done by using ridge or lasso regression. More on regularization If one cause for error in machine learning is variance, the other is bias. Attaining better predictive models involves reducing both of their impacts on the target function