Data Science Desktop Survival Guide by Graham Williams
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Chapter: ML Algorithms

20210103 We can think of algorithms for machine learning along three basic dimensions:

1. knowledge representation;
2. method or search heuristic;
3. measure of goodness.

This basic concept was introduced by 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.