Background: Patients with persistent atrial fibrillation (PsAF) exhibit a high recurrence rate following catheter ablation, and there is a lack of individualized prediction tools based on clinical ...
Abstract: Logistic regression is a widely utilized machine learning algorithm for binary classification tasks. In this study, the logistic regression algorithm is used to classify whether a disorder ...
ABSTRACT: Progress towards the fourth Millennium Development Goal - to reduce child mortality under the age of 5, to which all countries are committed - has been slow in several countries in the ...
eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end program that explains how to perform binary classification (predicting a variable with two possible discrete values) using ...
ABSTRACT: This research delves into the hurdles and strategies aimed at augmenting the market involvement of smallholder carrot farmers in Nakuru County, Kenya. Employing a Multinomial Logit (MNL) ...
choose a suitable regression model for assessing a specific research hypothesis using data collected from an epidemiological study, fit the model using standard statistical software, evaluate the fit ...
Abstract: Logistic regression is the main method to deal with data classification in the field of large data and machine learning. The traditional logistic regression uses gradient descent method to ...
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