Motivation and Background
A very important learning problem is the task of learning a concept. Concept learning has attracted much attention in learning theory. For having a running example, we look at humans who are able to distinguish between different “things,” e.g., chair, table, car, airplane, etc. There is no doubt that humans have to learn how to distinguish “things.” Thus, in this example, each concept is a thing. To model this learning task, we have to convert “real things” into mathematical descriptions of things. One possibility to do this is to fix some language to express a finitelist of properties. Afterward, we decide which of these properties are relevant for the particular things we want to deal with and which of them have to be fulfilled or not to be fulfilled, respectively. The list of properties comprises qualities or traits such as “has four legs,” “has wings,” “is...
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Zeugmann, T. (2011). PAC Learning. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_625
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