Linear Models, Data, Artificial Intelligence, Machine Learning.
marginally In summary, more regularization usually leads to lower training accuracy but generally increases test accuracy. sklearn uses L2 regularization as the default in Logistic Regression models. Below is an example of a model fit on a dataset with 30-ish predictors (x-axis) with the y-axis