The weighted priors approach for combining expert opinions in logistic regression experiments
نویسندگان
چکیده
منابع مشابه
An Ensemble Approach to Combining Expert Opinions
This paper introduces a new classification problem in the context of human computation. Given training data annotated by m human experts s.t. for each training instance the true class is provided, the task is to estimate the true class of a new test instance. To solve the problem we propose to apply a wellknown ensemble approach, namely the stacked-generalization approach. The key idea is to vi...
متن کاملCombining Expert Opinions∗
I analyze a model of advice with two perfectly informed experts and one decision maker. The bias of an expert is her private information. I show that consulting two experts is better than consulting just one. In the simple “peer review” mechanism, the decision maker receives just one report, and the second expert decides whether to block the first expert’s report. A more rigid peer review proce...
متن کاملDesigning Elicitor: Software to Graphically Elicit Expert Priors for Logistic Regression Models in Ecology. 2006
ELICITOR is graphical elicitation software created to elicit normal prior distributions for a Bayesian logistic regression model. Motivated by a real need to include expert knowledge in presence–absence models in ecology, this research describes a synthesis of theory from statistics, psychology and ecology. The aim was to build elicitation software that would be user friendly to environmental s...
متن کاملA NEW APPROACH FOR PARAMETER ESTIMATION IN FUZZY LOGISTIC REGRESSION
Logistic regression analysis is used to model categorical dependent variable. It is usually used in social sciences and clinical research. Human thoughts and disease diagnosis in clinical research contain vagueness. This situation leads researchers to combine fuzzy set and statistical theories. Fuzzy logistic regression analysis is one of the outcomes of this combination and it is used in situa...
متن کاملExperiments on logistic regression
In this report, several experiments have been conducted on a spam data set with Logistic Regression based on Gradient Descent approach. First, the overfitting effect is shown with basic settings (vanilla version). Then Stochastic Gradient Descent and 2-Norm Regularization techniques are both implemented with demonstration of the benefits of these two methods in preventing overfitting. Besides, ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Quality Engineering
سال: 2017
ISSN: 0898-2112,1532-4222
DOI: 10.1080/08982112.2017.1319956