There are various different classes of machine learning algorithms. As such, since algorithms can belong to multiple 'classes' or categories at the same time at a conceptual level, it is hard to specifically state that an algorithm belongs exclusively to a single class. In this section, we will briefly discuss a few of the most commonly used and well-known algorithms.
These include:
- Regression models
- Association rules
- Decision trees
- Random forest
- Boosting algorithms
- Support vector machines
- K-means
- Neural networks
Note that in the examples, we have shown the basic use of the R functions using the entire dataset. In practice, we'd split the data into a training and test set, and once we have built a satisfactory model apply the same on the test dataset to evaluate the model's performance.