Probability matching

Known as: Probability-matching 
Probability matching is a decision strategy in which predictions of class membership are proportional to the class base rates. Thus, if in the… (More)
Wikipedia

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2013
2013
The motivation of the proposed method is to solve typical problem for multiple object tracking like partial background change… (More)
Is this relevant?
2010
2010
Findings from two experiments indicate that probability matching in sequential choice arises from an asymmetry in strategy… (More)
  • figure 1
  • figure 2
  • figure 3
  • figure 4
  • figure 5
Is this relevant?
Highly Cited
2010
Highly Cited
2010
The question of which strategy is employed in human decision making has been studied extensively in the context of cognitive… (More)
  • figure 1
  • figure 2
  • table 1
Is this relevant?
2008
2008
First-order probability matching priors are priors for which Bayesian an d frequentist inference, in the form of posterior… (More)
  • table 1
Is this relevant?
2007
2007
Probability matching priors are priors for which Bayesian and frequentist inference, in the form of posterior quantiles, or… (More)
  • table 1
  • figure 1
Is this relevant?
Highly Cited
2005
Highly Cited
2005
Learning the optimal probabilities of applying an exploration operator from a set of alternatives can be done by self-adaptation… (More)
Is this relevant?
Review
2005
Review
2005
A probability matching prior is a prior distribution under which the posterior probabilities of certain regions coincide with… (More)
Is this relevant?
2005
2005
The paper considers priors obtained by ensuring approximate frequentist validity of (a) posterior quantiles, and of (b) the… (More)
Is this relevant?
Review
1998
Review
1998
The experimental phenomenon known as “probability matching” is often offered as evidence in support of adaptive learning models… (More)
  • table 1
  • table 2
  • table 3
  • table 4
  • table 5
Is this relevant?
1995
1995
We present a new algorithm for associative reinforcement learning. The algorithm is based upon the idea of matching a network's… (More)
  • figure 1
  • table 1
  • figure 2
  • table 3
Is this relevant?