The Use of Explanations for Similarity-based Learning
نویسنده
چکیده
Due to the difficult nature of Machine Learning, it has often been looked at in the context of " t o y " domains or in more realistic domains with simplifying assumptions. We propose an integrated learning approach that combines Explanation-Based and Similarity-Based Learning methods to make learning in an inherently complex domain feasible. We discuss the use of explanations for Similarity-Based Learning and present an example from a program which applies thee ideas to the domain of terrorist events.
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