Chapter 4
The Bias-Variance Trade-off
Section 2
Estimating the Coefficients and Intercepts of Logistic Regression
In the previous lesson, we learned that the coefficients of a logistic regression (each of which goes with a particular feature), and the intercept, are determined when the .fit method is called on a logistic regression model in scikit-learn using the training data. These numbers are called the parameters of the model, and the process of finding the best values for them is called parameter estimation. Once the parameters are found, the logistic regression model is essentially a finished product; therefore, with just these numbers, we can use the trained logistic regression in any environment where we can perform common mathematical functions. Here are the topics that we will cover now: