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Although most of us that have heard of or used regression modeling before tend to immediately think of its applications for predicting quantitative outcomes, regression modeling is actually quite robust and capable of also predicting qualitative, discrete outcomes like those found in classification problems. In fact, it is arguable that many traditional ML problems in business tend to be classification problems rather than regression ones. Therefore, we need to add some more regression techniques into our toolbox for just such occasions! In this chapter we will deepen your understanding of logistic regression with advanced concepts such as multiclass and multilabel classification, regularization, and model evaluation metrics.
In this chapter, we’re going to cover the following main topics:
- Overview of Logistic Regression
- Multiclass Classification Techniques
- Regularization in Logistic Regression
- Multilabel...
