Summary: The Bias-Variance Trade-Off
Explore the bias-variance trade-off in logistic regression by understanding model fitting with gradient descent, using regularization to prevent overfitting, and applying cross-validation to tune hyperparameters. This lesson prepares you to apply these core concepts in more advanced predictive models.
We'll cover the following...
We'll cover the following...
In this chapter, we introduced the final details of logistic regression and continued to understand how to use scikit-learn to fit logistic regression models. We gained more visibility into how the model fitting process works by learning about the concept of a cost function, which is minimized by the gradient descent procedure to estimate parameters during model fitting.
