A Computationally and Cognitively Plausible Model of Supervised and Unsupervised Learning

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    4 Citations (Scopus)

    Abstract

    Both empirical and mathematical demonstrations of the importance of chance-corrected measures are discussed, and a new model of learning is proposed based on empirical psychological results on association learning. Two forms of this model are developed, the Informatron as a chance-corrected Perceptron, and AdaBook as a chance-corrected AdaBoost procedure. Computational results presented show chance correction facilitates learning.

    Original languageEnglish
    Pages145-156
    Number of pages12
    DOIs
    Publication statusPublished - 23 Jul 2013
    EventInternational Conference on Brain Inspired Cognitive Systems -
    Duration: 9 Jul 2013 → …

    Conference

    ConferenceInternational Conference on Brain Inspired Cognitive Systems
    Period9/07/13 → …

    Keywords

    • AdaBoost
    • Chance-corrected evaluation
    • Kappa
    • Perceptron

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