High Cognitive Flexibility Learners Perform Better in Probabilistic Rule Learning
نویسندگان
چکیده
منابع مشابه
Probabilistic Rule Learning
Traditionally, rule learners have learned deterministic rules from deterministic data, that is, the rules have been expressed as logical statements and also the examples and their classification have been purely logical. We upgrade rule learning to a probabilistic setting, in which both the examples themselves as well as their classification can be probabilistic. The setting is incorporated in ...
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This paper describes PISCES 1.2E, a system for incremental learning of probabilistic rules. PISCES is efficiently incremental in the sense that both its processing time per instance and its memory usage are independent of the number of training instances. Classification accuracy alone does not provide a sufficient measure of performance for probabilistic classifiers. Additional measures include...
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Rule-based joint fuzzy and probabilistic networks
One of the important challenges in Graphical models is the problem of dealing with the uncertainties in the problem. Among graphical networks, fuzzy cognitive map is only capable of modeling fuzzy uncertainty and the Bayesian network is only capable of modeling probabilistic uncertainty. In many real issues, we are faced with both fuzzy and probabilistic uncertainties. In these cases, the propo...
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ژورنال
عنوان ژورنال: Frontiers in Psychology
سال: 2020
ISSN: 1664-1078
DOI: 10.3389/fpsyg.2020.00415