Generally, the process for fitting a logistic regression model using scikit-learn is very similar to that which you previously saw for statsmodels. One important exception is that scikit-learn will ...

Abstract: The logistic regression model is a linear model widely used for two-category classification problems. This report examines the enhancement and improvement methods of logistic regression ...

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

Objective: To develop and validate a logistic regression model predicting postoperative malnutrition risk in elderly patients using clinical, dietary, and nutritional data. Table 1. Comparison of ...

Department of Mathematics, Statistics and Actuarial Science, Faculty of Health, Natural Resources and Applied Sciences, Namibia University of Science and Technology, Windhoek, Namibia. Food insecurity ...

Abstract: Employee Well-being is the physical and psychological experience and feeling of employees during work, it is a critical indicator of employee's quality of life and plays an important role in ...

CLEVELAND, Tenn. (WATE) — The Trump administration’s tariffs on China are affecting the hobby industry, including one small business in East Tennessee. President Trump has implemented 145% tariffs on ...

Objective: We aimed at establishing a predictive model for poor long-term prognosis (3 months post-treatment) following endovascular treatment (EVT) for severe acute ischemic stroke (AIS) and ...