What is an intuitive way of explaining how to set Hyperparameters for Regularization? How would these hyperparameters change for L1 or L2 Regularization?

In Python I have seen np.logspace() used to create the "C space" which is then stored in a dictionary called "parameter grid" which is then used within grid search for a model (i.e. logistic regression).


closed as too broad by whuber Jan 11 at 21:55

Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.