Culicoides imicola is the main vector of the bluetongue virus in theMediterranean Basin. Spatial distribution models for this species traditionally employ either climatic data or remotely sensed data, or a combination of both. Until now, however, no studies compared the accuracies of C. imicola distribution models based on climatic versus remote sensing data, even though remotely sensed dataset...

This paper describes a novel methodology for predicting fault prone modules. The methodology is based on Dempster-Shafer (D-S) belief networks. Our approach consists of three steps: First, building the Dempster-Shafer network by the induction algorithm; Second, selecting the predictors (attributes) by the logistic procedure; Third, feeding the predictors describing the modules of the current pr...

The paper presents a study of how the detailed history of communication between a sales agent and a customer can be used to estimate the probability of success (sale). It utilizes the data obtained from a Minnesota based company that uses telesales in a business-to-business environment. Extensive telesales database was investigated and principal variables influencing the sale event were determi...

The failure rate of Small and medium enterprises (SMEs), is high in Sweden. Around 6000 SMEs go into bankruptcy every year. This paper attempts to identify the main determinants that are perceived to have contribution to the failure of Swedish SMEs. The research is in principle based on the analysis of panel data matched sample consisting of 1991 bankrupted and 1991 nonbankrupted Swedish SMEs. ...

EMPs Extended morphological profiles EMPs Extended morphological profiles LDA Linear discriminant analysis LogDA Logarithmic discriminant analysis MLR Multinomial logistic regression MLRsubMRF Subspace-based multinomial logistic regression followed by Markov random fields MPs Morphological profiles MRFs Markov random fields PCA Principal component analysis QDA Quadratic discriminant analysis RH...

Discriminant analysis is an effective methodology to deal with the classification problem. However, most common methods including binary logistic regression in discriminant analysis rarely consider the semantics explanations such as losses or costs in decision rules. From the idea of three-way decisions in decision-theoretic rough sets (DTRS), we propose a new discriminant analysis approach by ...

Methods for discriminant analysis were compared with respect to classification accuracy under nonnormality through Monte Carlo simulation. The methods compared were linear discriminant analyses based both on raw scores and on ranks; linear logistic discrimination; and mixture discriminant analysis. Linear discriminant analysis and linear logistic discrimination were suboptimal in a number of sc...

We determine market segments by clustering households on the basis of their average choice elasticities across purchases and brands w.r.t. price, sales promotion and brand loyalty. The cluster analysis technique used is a maximum likelihood method which allows varying size and orientation and assumes constant volume. Elasticities originate from choice models with alternatively linear and nonlin...

  Background: Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population.   Methods : In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were ...