Statistical Theory for Classification

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Hartigan 9704327 I explore the role of classification in probability and statistics. I use probability models in forming and validating classes, and in identifying modes and other new objects, but I also use classification for prediction and forming probability models. For example, in recognition problems, people compare new objects with classes of known objects, and predict behavior of these new objects by assigning the new objects to the classes and expecting the objects to behave similarly to known objects in those classes. I consider how properly formed classes may be used for understanding and prediction. For example, in congressional voting, members form a series of semi-permanent alliances or blocs that vote together on certain classes of issues. The size and constitution of these blocs offers a way to study the evolution of Congress.