18 ML Algorithms
20210103 We can think of algorithms for machine learning along three basic dimensions:
- knowledge representation (the language used to represent models);
- method or search heuristic (how to search different models);
- measure of goodness (how do we know we have a good model).
This basic concept was introduced in (Graham J. Williams 2011) characterising different artificial intelligence and machine learning algorithms in terms of the target language for representing knowledge, how the search space defined by the language is navigated to express sentences in the language, and how the sentences are measured to determine whether we have a good sentence.
In this chapter we present a range of machine learning algorithms, relating them to these dimensions, and demonstrating the algorithms in action.
References
Williams, Graham J. 2011. Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery. Use R! New York: Springer.
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