Multinomial Logistic Regression With Python
Multinomial logistic regression is an extension of logistic regression that adds native support for multi-class classification problems.
Logistic regression, by default, is limited to two-class classification problems. Some extensions like one-vs-rest can allow logistic regression to be used for multi-class classification problems, although they require that the classification problem first be transformed into multiple binary classification problems.
Instead, the multinomial logistic regression algorithm is an extension to the logistic regression model that involves changing the loss function to cross-entropy loss and predict probability distribution to a multinomial probability distribution to natively support multi-class classification problems.
In this tutorial, you will discover how to develop multinomial logistic regression models in Python.
After completing this tutorial, you will know:
- Multinomial logistic