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 Machine Learning



The Computer Revolution in Philosophy

Classics

"Computing can change our ways of thinking about many things, mathematics, biology, engineering, administrative procedures, and many more. But my main concern is that it can change our thinking about ourselves: giving us new models, metaphors, and other thinking tools to aid our efforts to fathom the mysteries of the human mind and heart. The new discipline of Artificial Intelligence is the branch of computing most directly concerned with this revolution. By giving us new, deeper, insights into some of our inner processes, it changes our thinking about ourselves. It therefore changes some of our inner processes, and so changes what we are, like all social, technological and intellectual revolutions." This book, published in 1978 by Harvester Press and Humanities Press, has been out of print for many years, and is now online, produced from a scanned in copy of the original, digitised by OCR software and made available in September 2001. Since then a number of notes and corrections have been added. Atlantic Highlands, NJ: Humanities Press.




Models of learning systems

Classics

"The terms adaptation, learning, concept-formation, induction, self-organization, and self-repair have all been used in the context of learning system (LS) research. The research has been conducted within many different scientific communities, however, and these terms have come to have a variety of meanings. It is therefore often difficult to recognize that problems which are described differently may in fact be identical. Learning system models as well are often tuned to the require- ments of a particular discipline and are not suitable for application in related disciplines."In Encyclopedia of Computer Science and Technology, Vol. 11. Dekker


A model based method for computer aided medical decision making

Classics

"A CASNET model consists of three main components: observations of a patient, pathophysiological states, and disease classifications. As observations are recorded, they are associated with the appropriate intennediate states. These states, in turn, are typically causally related, thereby forming a network that summarizes the mechanisms of disease. It is these patterns of states in the network that are linked to individual disease classes." Artificial intelligence, August, 1978. Reprinted in Clancey & Shortliffe. Readings in Medical Artificial Intelligence: The First Decade. Ch. 7.



An experiment on inductive learning in chess end games.

Classics

In E. W. Elcock and D. Michie (Eds.), Machine intelligence 8. New York: Wiley.



Maximum likelihood from incomplete data via the EM algorithm

Classics

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