A machine learning model may help predict mortality for hospitalized patients with cirrhosis at the time of admission, ...

BACKGROUND: Fontan circulatory failure (FCF) is a chronic state in palliated single ventricle heart disease with high morbidity and mortality rates, including heart failure, multisystem end-organ ...

After screening predictive variables by LASSO regression, three predictive models selected using the LazyPredict package, namely logistic regression (LR), support vector machine (SVM) and random ...

Forest Chase Reinildo in Crowded Race for Atletico Madrid Veteran Premier League clubs test Reinildo’s resolve At 31, Reinildo Mandava finds himself courted by an unlikely mix of ambition and ...

In the specific paper's context, the main aim is to use the logistic regression data set to look into the forecast of the failed escalator through the random forest machine learning algorithm.

Article citations More>> Kirasich, K., Smith, T. and Sadler, B. (2018) Random Forest vs Logistic Regression: Binary Classification for Heterogeneous Datasets. SMU Data Science Review, 1, Article 9.

Experiment in floodplain forest: Using tree mortality to support oak regeneration Date: April 16, 2025 Source: Universität Leipzig Summary: The pedunculate oaks typical of Leipzig's floodplain ...

Rajbharath, R., Sankari, I. and Scholar, P. (2017) Predicting Breast Cancer Using Random Forest and Logistic Regression. International Journal of Engineering Science and Technology, 7, 10708-10713.

Nottingham Forest are plotting an audacious move for Lookman, according to GMS sources, and they have been given hope that a deal will be possible as it is looking almost certain that he will walk ...

This research aims to compare the performance of Logistic Regression and Random Forest algorithms in classifying cyber-attack types. Using a data set consisting of 494,021 data points with 42 ...