The logistic regression algorithm is one of the most interpretable algorithms in the world of machine learning, and although the word "regression" implies predicting a numerical outcome, the logistic regression algorithm is, used to predict categories and solve classification machine learning problems.
In this chapter, you will learn about the following:
- How the logistic regression algorithm works mathematically
- Implementing and evaluating your first logistic regression algorithm with scikit-learn
- Fine-tuning the hyperparameters using GridSearchCV
- Scaling your data for a potential improvement in accuracy
- Interpreting the results of the model
Logistic regression has a wide range of applications, especially in the field of finance, where building interpretable machine learning models is key in convincing both investors...
