Summary: Details of Logistic Regression and Feature Extractor
Explore how to evaluate features using univariate methods like Pearson correlation and ANOVA F-test, and learn the fundamentals of logistic regression including the sigmoid function and decision boundaries. This lesson helps you communicate predictive insights clearly and prepares you to apply logistic regression effectively in real-world projects.
We'll cover the following...
We'll cover the following...
In this chapter, we have learned how to explore features one at a time, using univariate feature selection methods including Pearson correlation and an ANOVA F-test. While looking at features in this way does not always tell the whole story, because you are potentially missing out on important interactions between features, it is often a helpful step.
Understanding the ...