LOGISTIC regression analysisMATHEMATICAL modelsAt present, air pollution is a major problem in the upper northern region of Thailand. Air pollutants have an effect on human health, the economy and the traveling
In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under ...
We obtained a trial-by-trial estimate of subjectsʼ behavioral policy using a logistic regression predicting current trial choice, using the history of choices, rewards and choice × reward interactions (Fig. 6a). This gave an estimate on each trial of the probability that the animal would cho...
Sparse Logistic regression ✕ ✕ Why celer? celer is specially designed to handle Lasso-like problems which makes it a fast solver of such problems. In particular it comes with tools such as: automated parallel cross-validation support of sparse and dense data optional feature centering and no...
In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under ...
On the multivariable logistic regression, variables with p-value < 0.5 were considered as they had statistically significant association with breast problem. The overall prevalence of breast problems among postnatal lactating women was 54.3% (95%, CI 49.3–59.3%). Primipara (AOR = 5.09; ...
We introduce an imbalanced data classification approach based on logistic regression significant discriminant and Fisher discriminant. First of all, a key indicators extraction model based on logistic regression significant discriminant and correlation analysis is derived to extract features for customer classif...
The algorithm is evaluated on various synthetic and real data, and the efficiency is demonstrated particularly on 1 regularized convex/nonconvex quadratic programs and logistic regression problems.doi:10.1007/s10915-020-01364-0Chungen ShenWenjuan Xue...
Univariate logistic regression analysis was used first to evaluate the effect of variables on the exposure to triad combination of PP, PIM and DDI. Factors determined as significant variables from univariate logistic analysis (significance set at p<0.05 level), age, gender, numbe...
If Y is continuous, the learning program is a regression problem. The focus of this paper is on regression where the goal is to accurately predict continuous responses. There have been extensive studies on weighted ensembles in the literature. The proposed approaches can be divided into constant ...