Meta-inductive Probability Aggregation and Optimal Scoring
نویسندگان
چکیده
In this paper we combine the theory of probability aggregation with results of machine learning theory concerning the optimality of predictions under expert advice. In probability aggregation theory several characterisation results for linear aggregation exist. However, in linear aggregation weights are not fixed, but free parameters. We show how fixing such weights by successbased scores allows for transferring the mentioned optimality results to the case of probability aggregation.
منابع مشابه
Acceptance, Aggregation and Scoring Rules
This article provides a novel perspective on the vexed issue of the relation between probability and rational acceptability, exploiting a recently-noted structural parallel with the problem of judgment aggregation. After offering a number of general desiderata on the relation between finite probability models and sets of accepted sentences in a Boolean sentential language, it is noted that a nu...
متن کاملASSOCIATED PROBABILITY INTUITIONISTIC FUZZY WEIGHTED OPERATORS IN BUSINESS START-UP DECISION MAKING
In the study, we propose the Associated Probability Intuitionistic Fuzzy Weighted Averaging (As-P-IFWA) and the Associated Probability Intuitionistic Fuzzy Weighted Geometric (As-P-IFWG) aggregation operators with associated probabilities of a fuzzy measure presenting an uncertainty. Decision makers' evaluations are given as intuitionistic fuzzy values and are used as the arguments of the aggre...
متن کاملNo Free Lunch Theorem , Inductive Skepticism , and the Optimality of Meta - Induction Word count : 4986
The no free lunch theorem (Wolpert 1996) is a radicalized version of Hume's induction skepticism. It asserts that relative to a uniform probability distribution over all possible worlds, all computable prediction algorithms whether 'clever' inductive or 'stupid' guessing methods (etc.) have the same expected predictive success. This theorem seems to be in conflict with results about meta-in...
متن کاملScore Aggregation via Spectral Method
The score aggregation problem is to find an aggregate scoring over all candidates given individual scores provided by different agents. This is a fundamental problem with a broad range of applications in social choice and many other areas. The simple and commonly used method is to sum up all scores of each candidate, which is called the sumup method. In this paper, we give good algebraic and ge...
متن کاملAn Optimal Design Approach for Resistive and Inductive Superconducting Fault Current Limiters via MCDM Techniques
The design process of a superconducting current limiter (SFCL) requires simulation and definition of its electrical, magnetic and thermal properties in form of equivalent circuits and mathematical models. However, any change in SFCL parameters: dimension, resistance, and operating temperature can affect the limiting mode, quench time, and restore time. In this paper, following the simulation of...
متن کامل