Comparison of logistic regression and random forest algorithms for airport’s runway assignment

Comparison of Random Forest and Logistic Regression Methods in Predicting Mortality in Colorectal Cancer Patients and its Related Factors

Background and Objectives: The purpose of this study was to predict the mortality rate of colorectal cancer in Iranian patients and determine the effective factors  on the mortality of patients with colorectal cancer using random forest and logistic regression methods.   Methods: Data from 304 patients with colorectal cancer registry from the Gastroenterology and Liver Research Center of Shah...

A Comparison of Logistic Regression to Random Forests For

Random forest versus logistic regression: a large-scale benchmark experiment

The Random Forest (RF) algorithm for regression and classification has considerably gained popularity since its introduction in 2001. Meanwhile, it has grown to a standard classification approach competing with logistic regression in many innovation-friendly scientific fields. In this context, we present a large scale benchmarking experiment based on 260 real datasets comparing the prediction p...

Evaluation of risk factors of recurrence of hodgkin\'s lymphoma using random survival forest and comparison with cox regression model

Background: In many studies, Cox regression was used to assess the important factors that affect the survival of cancer patients based on demographic and clinical variables. The aim of this study was to determine the factors affecting the survival of patients with Hodgkin's lymphoma using the random survival forest (RSF) method and compare it with the Cox model. Methods: In this retrospective ...

Comparison of ordinary logistic regression and robust logistic regression models in modeling of pre-diabetes risk factors

Background: Regarding the increased risk of developing type 2 diabetes in pre-diabetic people, identifying pre-diabetes and determining of its risk factors seems so necessary. In this study, it is aimed to compare ordinary logistic regression and robust logistic regression models in modeling pre-diabetes risk factors. Methods: This is a cross-sectional study and conducted on 6460 people, over ...