The rule conflict is an important issue for associative classification due to a large set of rules. In this paper, a new approach called Associative Classification with Bayes (AC-Bayes) is proposed. To address rule conflicts, AC-Bayes has two distinguished features: (1) Associative classification is improved. (2) Naïve Bayesian model is applied in process of classification. A small set of high ...

Despite its normative appeal and widespread use, Bayes’ rule has two well-known limitations: first, it does not predict how agents should react to an information to which they assigned probability zero; second, a sizable empirical evidence documents how agents systematically deviate from its prescriptions by overreacting to information to which they assigned a positive but small probability. By...

Despite its normative appeal and widespread use, Bayes’ rule has two well-known limitations: first, it does not predict how agents should react to an information to which they assigned probability zero; second, a sizable empirical evidence documents how agents systematically deviate from its prescriptions by overreacting to information to which they assigned a positive but small probability. By...

Abstract Bayes estimators of the scale parameter of a generalized gamma type model are obtained for different priors. For the proposed prior, Bayes estimator of θ for given p and k=1 coincides with MLE of θ if c=2, whereas Bayes estimator of hazard rate function of θ given p and k coincides with its MLE. Thumb’s rule has been used for constructing a conjugate prior for θ . Bayes estimators of r...

This paper states necessary and sufficient conditions for the existence, uniqueness, and updating according to Bayes’ rule, of subjective probabilities representing individuals’ beliefs. The approach is preference based, and the result is an axiomatic subjective expected utility model of Bayesian decision making under uncertainty with statedependent preferences. The theory provides foundations ...

We propose a modular neural-network structure for implementing the Bayesian framework for learning and inference. Our design has three main components, two for computing the priors and likelihoods based on observations and one for applying Bayes’ rule. Through comprehensive simulations we show that our proposed model succeeds in implementing Bayesian learning and inference. We also provide a no...

Jamal and Sunder (1996) showed that the median prices in double auctions populated by zero-intelligence (ZI) traders whose trading limits are set by two biased heuristics tend to converge to the same equilibrium as if their trading limits were set by applying Bayes’ Rule. This note provides an analytical explanation of why the repeated use of biased heuristics approximates Bayes rule. JEL class...

The statistical behavior of clutter observed near grazing incidence and at 95 GHz is investigated for the specific cases of bare ground, snow-cover, and for a heterogeneous scene. The bare ground constitutes a homogeneous target under homogeneous conditions and the magnitude of the amplitude is Rayleigh distributed. While the snow-cover is a homogeneous target, the conditions under which it was...