In order to induct a Bayesian network from data, researchers proposed a variety of score metrics based on different assumptions. The score metric that performs best is of interest. In this paper, we compared the performance of five score metrics: UPSM, CUPSM, DPSM, BDe, and MDL; resulting from five different assumptions: uniform prior, conditional uniform prior, Dirichlet prior, likelihood equi...

The propensity score is a subject's probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated and untreated subjects have similar distributions of observed baseline covariates. Propensity-score matching is a popular method of using the propensity score in the medical literature. Using this approach, matched sets of treated and untre...

this paper deals with the problem of optimizing two-stage structure decision making units (dmus) where the activity and the performance of two-stage dmu in one period effect on its efficiency in the next period. to evaluate such systems the effect of activities in one period on ones in the next term must be considered. to do so, we propose a dynamic dea approach to measure the performance of su...

This paper describes the participation of CERTH in the Social Event Detection Task of MediaEval 2014. For Challenge 1, we use a“same event model”to construct a graph on which we perform community detection to obtain the final clustering. Importantly, we tune the model to have a higher true positive rate than true negative rate, leading to significantly improved performance. The F1 score and NMI...

The most popular unidimensional psychological test evaluation rule is the trivial scoring function: To the answers of each item of a test item scores of 0,1,...m points are awarded and the unweighted or simple or total sum of the item scores gives the test score (also: Likert score). This total score has desirable stochastic ordering properties like monotone likelihood ratio (MLR), stochastic o...