The power of the classification methods is due to the quality of its algorithms, which have been improved and updated over the years. These are divided into several main types, depending on the nature of the signal used for learning or the type of feedback adopted by the system.
They are as follows:
- Supervised learning: The algorithm generates a function that links input values to a desired output through the observation of a set of examples, in which each piece of data that's input has its relative output data. This is used to construct predictive models.
- Unsupervised learning: The algorithm tries to derive knowledge from a general input, without the help of a set of preclassified examples, which are used to build descriptive models. Typical examples of the application of these algorithms are search engines.
The following diagram shows...