background: the purpose of this investigation was to compare empirically predictive ability of an artificial neu­ral network with a logistic regression in prediction of low back pain. methods: data from the second national health survey were considered in this investigation. this data in­cludes the information of low back pain and its associated risk factors among iranian people aged 15 years a...

this study aims at comparing the performance of logistic regression, maximum entropy, and multilayer perceptron techniques in preparing the predictive habitat distribution map of amygdalus scoparia in rangelands of qom province. for this purpose, vegetation sampling was done using random systematic methods after identifying pure habitats of this species. for soil sampling, eight profiles were e...

This paper considers logistic regression analysis with linked data. It is shown that, in logistic regression analysis with linked data, a finite mixture of Bernoulli distributions can be used for modeling the response variables. We proposed an iterative maximum likelihood estimator for the regression coefficients that takes the matching probabilities into account. Next, the Bayesian counterpart...

An imbalanced data problem occurs in the absence of a good class distribution between classes. Imbalanced will cause classifier to be biased majority as standard classification algorithms are based on belief that training set is balanced. Therefore, it crucial find can deal with for any given task. The aim this research best method among AdaBoost, XGBoost, and Logistic Regression simulated data...

the performance of different yield loss models from an exponential family was evaluated in safflower-redroot pigweed systems in two field experiments conducted during 2007 and 2008 growing seasons at the research field of agricultural college of shiraz university, iran. the yield loss of safflower was recorded as relative yield loss in experimental plots laid out in split plot design with three...