Other prominent classification algorithms:
- Naive Bayes and other probabilistic approaches,
- Support Vector Machines (SVMs) and other kernel methods,
- (Artificial) (Deep) Neural Networks.
Interestingly, in the next chapter we will note that the logistic regression model is a special case of a feed-forward single layer neural network.
We will also generalise the binary logistic regression to the case of a multiclass classification.
The state-of-the art classifiers called Random Forests and XGBoost (see also: AdaBoost) are based on decision trees. They tend to be more accurate but – at the same time – they fail to exhibit the decision trees’ important feature: interpretability.
Trees can also be used for regression tasks, see R package