Artificial intelligence and statistics, Volume 1
A statistical view of uncertainty in expert systems. Knowledge, decision making, and uncertainty. Conceptual clustering and its relation to numerical taxonomy. Learning rates in supervised and unsupervised intelligent systems. Pinpoint good hypotheses with heuristics. Artificial intelligence approaches in statistics. REX review. Representing statistical computations: toward a deeper understanding. Student phase 1: a report on work in progress. Representing statistical knowledge for expert data analysis systems. Environments for supporting statistical strategy. Use of psychometric tools for knowledge acquisition: a case study. The analysis phase in development of knowledge based systems. Implementation and study of statistical strategy. Patterns in statisticalstrategy. A DIY guide to statistical strategy. An alphabet for statistician's expert systems.
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A Statistical View of Uncertainty in Expert Systems
Knowledge Decision Making and Uncertainty
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algorithms amphibian-1 applied approach Artificial Intelligence assumptions backward chaining chapter choice CLUSTER/2 concepts conceptual clustering constructed context data analysis data set data structure data-flow decision dependent described discriminant discussion distribution domain evidence example expert systems expertise explanation exploratory data analysis Figure formal frame function Gale given graph HANDICAPPER heuristics hierarchical horse human hypothesis implementation inference engine interaction interpretation interview knowledge engineer knowledge representation knowledge-based learning linear linear regression logical machine learning MANOVA methods Michalski module multidimensional scaling MYCIN node numerical taxonomy object set packages particular partition plot points possible Pregibon probabilistic probability problem procedures questions reasoning regression analysis represent representation rules selected slot specific stage statistical expert systems statistical strategy statistician Student subsets subtasks suggested task techniques theory transformations Tversky uncertainty UNIMEM unsupervised learning variable weight