In various application areas, prior information is available about the direction of the effects of multiple predictors on the conditional response distribution. For example, in epidemiology studies of potentially adverse exposures and continuous health responses, one can typically assume a priori that increasing the level of an exposure does not lead to an improvement in the health response. Su...

This paper describes the iLab-Edinburgh Sentiment Analysis system, winner of the Arabic Twitter Task 7 in SemEval-2016. The system employs a hybrid approach of supervised learning and rule-based methods to predict a sentiment intensity (SI) score for a given Arabic Twitter phrase. First, the supervised method uses an ensemble of trained linear regression models to produce an initial SI score fo...

Summary Regression analysis methods, such as linear regression for continuous outcomes and logistic binary outcomes, have been widely used in medical research data many years. However, there instances of misconceptions misinterpretations results within the community. Univariate multiple analyses are commonly by publications to identify factors that significantly correlated with outcome. In this...

This paper introduces multiple instance regression, a variant of multiple regression in which each data point may be described by more than one vector of values for the independent variables. The goals of this work are to (1) understand the computational complexity of the multiple instance regression task and (2) develop an efficient algorithm that is superior to ordinary multiple regression wh...

introduction: studying long-term trend changes of meteorological parameters is one of the routine methods in atmospheric studies, especially in the climate change subject. among the meteorological parameters, temperature is always considered as one of the most atmospheric elements and studying it in order to gain a better understanding of the climate change phenomenon, has been effective. in ad...