in this study, an effort has been made to determine the most important risk factors of tuberculosis (tb) in district mardan. a total of 645 cases were examined, and their personal and medical data were collected. for each case, the phenomenon of tb was studied in relation to different risk factors. statistical techniques of logistic regression and backward elimination procedure were used to ana...

Statistical models are simple mathematical rules derived from empirical data describing the association between an outcome and several explanatory variables. In a typical modeling situation statistical analysis often involves a large number of potential explanatory variables and frequently only partial subject-matter knowledge is available. Therefore, selecting the most suitable variables for a...

The present study aims to model systematic risk using financial and accounting variables. Accordingly, the data for 174 companies in Tehran Stock Exchange are extracted for the period of 2006 to 2016. First, the systematic risk index is estimated using the ARFIMA-FIGARCH model. Then, based on the research background, 35 affective financial and accounting variables are simultaneously used with t...

The search space for the feature selection problem in decision tree learning is the lattice of subsets of the available features. We provide an exact enumeration procedure of the subsets that lead to all and only the distinct decision trees. The procedure can be adopted to prune the search space of complete and heuristics search methods in wrapper models for feature selection. Based on this, we...

For dynamic games we consider the idea that a player, at every stage of the game, believes that his opponents will choose rationally in the future. Not only this, we also assume that players, throughout the game, believe that their opponents always believe that their opponents will choose rationally in the future, and so on. This leads to the concept of common belief in future rationality, whic...

We consider constrained optimization problems defined in the tropical algebra setting on a linearly ordered, algebraically complete (radicable) idempotent semifield (a semiring with addition and invertible multiplication). The are to minimize objective functions given by analogues of multivariate Puiseux polynomials, subject box constraints variables. A technique for variable elimination is pre...

We present and study the Contribution-Selection algorithm (CSA), a novel algorithm for feature selection. The algorithm is based on the Multiperturbation Shapley Analysis, a framework which relies on game theory to estimate usefulness. The algorithm iteratively estimates the usefulness of features and selects them accordingly, using either forward selection or backward elimination. Empirical co...

We present and examine a novel Contribution-Selection algorithm (CSA) for feature selection based on the Multi-perturbation Shapley Analysis. The algorithm combines both the filter and wrapper approaches in a multi-phasic manner to estimate features’ usefulness and select them accordingly, either using forward selection or backward elimination. Empirical comparison of several feature selection ...