A computationally and cognitively plausible model of supervised and unsupervised learning
Powers, David Martin
Copyright © 2013 Springer-Verlag Berlin Heidelberg
Springer-Verlag Berlin Heidelberg
The issue of chance correction has been discussed for many decades in the context of statistics, psychology and machine learning, with multiple measures being shown to have desirable properties, including various definitions of Kappa or Correlation, and the psychologically validated ΔP measures. In this paper, we discuss the relationships between these measures, showing that they form part of a single family of measures, and that using an appropriate measure can positively impact learning.
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Powers, D.M. (2013). A computationally and cognitively plausible model of supervised and unsupervised learning. In D Liu et. al (Ed.), Advances in Brain Inspired Cognitive Systems: Vol 7888, 6th International Conference, BICS 2013, Beijing, China, June 9-11, 2013. Proceedings (pp. 145-156) Berlin: Springer Berlin Heidelberg.