… Random forest, logistic regression, and Knearest neighbor were … We used the chi-square
test as a statistical measure to … technique called label encoding to convert our categorical data …

… mortality in the ICU using logistic regressions, and its effect on … -square tests for categorical
variables, Mann Whitney tests for … The multiple imputation procedure converged and imputed …

… correlation test, hypothesis testing and random forest methods, … Categorical variables were
analyzed by χ2 test, while … , we performed the binary logistic regression analysis. ROC curves …

… Categorical variables were expressed as … procedure. MAFLD, age, alcohol intake, and
smoking status were selected as explanatory variables for the logistic regression analysis. In …

… with significant fibrosis were analysed by logistic regression … Categorical variables are
expressed as frequencies and … In addition, this method overcomes the constraints of linear models …

… categorical variables when MRMR was performed in this study. … Logistic regression is a
statistical method for analyzing a … and testing groups, the feature selection method, decision tree …

… standard methods (ie, logistic regression, stepwise regression, … Creating categorical
variables allows for the modeling of … t test for continuous variables and the χ 2 test for categorical …

… Dummy variables were used for the categorical variables: … Simple logistic regression was
used to identify significant … that Pap smear tests were the best method to detect cervical cancer, …

… The ensemble model was tested using 70% and validated … of terms and x is the categorical
variables. H m is the baseline … stepwise and enter logistic regression method have been …

… grouped random parameters logit model in three out of the four … significance were tested
based on a stepwise method. … (for categorical variables) considering that these variables are still …