The evolution of the Machine Learning field is characterized by a great expansion and diversification of learning methods. Most of the research has been orientated toward single-strategy learning methods that apply one primary type of inference, such as induction, deduction or analogy, and one representational mechanism, such as predicate calculus or neural network. Such methods include those for empirical inductive generalization explanation-based learning, learning by abduction, case-based learning, qualitative methods for law discovery, conceptual clustering, neural network learning, and others.
edited by Ryszard S. Michalski and Gheorghe Tecuci
Machine Learning, Multistrategy Learning Systems
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