How-To Geek on MSN

How to run R-style linear regressions in Python the easy way

If you have experience with R or want a quick way to generate a regression with statsmodels using a pandas DataFrame, you can ...
IEEE

Efficient Abstraction of Healthcare Data for Real-Time Decision Making Using Logistic Regression and Linear Regression

Abstract: Data analytics can help drive decision-making and improve patient outcomes in healthcare. But of course, healthcare data is complex, and the process to access & analyze it can be slow. Here, ...
IEEE

An Explainable AI Approach to Sentiment Analysis of Twitter Data Using Logistic Regression and Random Forest

Abstract: Social media platforms such as Twitter and Facebook have transformed communication by enabling users to share opinions and thoughts instantly. These platforms generate vast amounts of text ...
Scientific Research Publishing

Lelisho, M.E., Wogi, A.A. and Tareke, S.A. (2022) Ordinal Logistic Regression Analysis in Determining Factors Associated with Socioeconomic Status of Household in Tepi Town ...

ABSTRACT: Food insecurity is a global issue, and households in a society can experience food insecurity at different levels that could range from being mildly food insecure to severely food insecure.
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Build Logistic Regression From Scratch In Python – You Won'T Believe How Easy It Is!

Learn how to implement Logistic Regression from scratch in Python with this simple, easy-to-follow guide! Perfect for beginners, this tutorial covers every step of the process and helps you understand ...
Albert Lea Tribune

How to Manage the Logistic Regression Tool

Using data to make smart decisions is powerful—but only if you know how to manage the tools behind it. Logistic regression, one of the most widely used methods in data analysis,... Using data to make ...
Frontiers

Comparison between traditional logistic regression and machine learning for predicting mortality in adult sepsis patients

Background: Sepsis is a life-threatening disease associated with a high mortality rate, emphasizing the need for the exploration of novel models to predict the prognosis of this patient population.