TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
IEEE

Churn Rate Prediction System using Logistic Regression, SVM, and Random Forest Models

Abstract: Customers are the life blood of any business, and their importance cannot be overstated. Customers are a business’s primary source of revenue. Retaining and gaining new clients is crucial to ...
The Lancet

Forecasting left ventricular systolic dysfunction in heart failure with artificial intelligence

aDepartment of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA bResearch Laboratory for Electronics, Massachusetts Institute of Technology ...
GitHub

Nonlinear Model-Predictive Control Using Koopman Operator

This document provides a detailed explanation of the MATLAB code that demonstrates the application of the Koopman operator theory for controlling a nonlinear system using Model Predictive Control (MPC ...
Frontiers

Correlation between atrial cardiomyopathy and total burden of cerebral small vessel disease in patients with acute ischemic stroke

Background: Atrial cardiomyopathy (ACM) and cerebral small vessel disease (CSVD) share common risk factors (e.g., hypertension, diabetes, dyslipidemia, aging) and pathophysiological mechanisms (e.g., ...
Frontiers

Predictors of initiating high-efficacy vs. platform therapies as first-line disease-modifying treatment in multiple sclerosis

Multivariable logistic regression analysis was performed to identify factors independently associated with the use of heDMT as the first-line treatment. Ordinal logistic regression was used to examine ...
IEEE

Approximately Unimodal Likelihood Models for Ordinal Regression

Ordinal regression (OR, also called ordinal classification) is classification of ordinal data, in which the underlying target variable is categorical and considered to have a natural ordinal relation ...