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BAYES, Thomas (1702-61). An essay towards solving a problem in the doctrine of chances. Extract from Philosophical Transactions 53 (1763): 370-418.
Details
BAYES, Thomas (1702-61). An essay towards solving a problem in the doctrine of chances. Extract from Philosophical Transactions 53 (1763): 370-418.
4o. Quarter morocco, marbled boards.
FIRST EDITION of the first statement of Bayes's Theorem for calculating "inverse probabilities," which forms the basis for methods of decision analysis, statistical learning machines, and Bayesian networks. Bayesian networks are complex diagrams that organize the body of knowledge in any given area by mapping out cause-and-effect relationships among key variables and encoding them with numbers that represent the extent to which one variable is likely to affect another. Programmed into computers, these systems can automatically generate optimation predictions or decisions even when key pieces of information are missing. Bayesian or subjective decision theory is arguably the most comprehensive theory of decision-making; however, until the late 1980s, it had little application due to the stupefying complexity of the mathematics involved. The rapid advances in computing power and the development of key mathematical equations during the late 1980s and early 1990s made it possible to compute Bayesian networks with enough variables to be useful in practical applications. OOC 1.
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FIRST EDITION of the first statement of Bayes's Theorem for calculating "inverse probabilities," which forms the basis for methods of decision analysis, statistical learning machines, and Bayesian networks. Bayesian networks are complex diagrams that organize the body of knowledge in any given area by mapping out cause-and-effect relationships among key variables and encoding them with numbers that represent the extent to which one variable is likely to affect another. Programmed into computers, these systems can automatically generate optimation predictions or decisions even when key pieces of information are missing. Bayesian or subjective decision theory is arguably the most comprehensive theory of decision-making; however, until the late 1980s, it had little application due to the stupefying complexity of the mathematics involved. The rapid advances in computing power and the development of key mathematical equations during the late 1980s and early 1990s made it possible to compute Bayesian networks with enough variables to be useful in practical applications. OOC 1.
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