International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

IIT Madras Free Machine Learning, AI Course 2026: Registration Open, Apply Here

Learners who wish to receive a certificate must register for the exam scheduled on April 17, 2026, which will be conducted in two sessions - 9:30 am to 12:30 pm and 2 pm to 5 pm ...
Scientific Research Publishing

Johnson, A. and Lee, M. (2022) Predictive Modeling for Cardiovascular Risk Assessment Using Logistic Regression and Deep Learning. Journal of Biomedical Informatics, 130 ...

ABSTRACT: Heart disease remains one of the leading causes of mortality worldwide, accounting for millions of deaths annually. Early detection of individuals at risk is essential for reducing ...
Frontiers

Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults

Background: The health burden of diabetes mellitus and osteoporosis (DM-OP) comorbidity in the aging population is increasing, and dietary factors are modifiable risk determinants. This study ...
Scientific Research Publishing

Heart Disease Prediction: A Logistic Regression Approach ()

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 ...
IEEE

Machine Learning–Based Hypertension Risk Stratification Using Logistic Regression and XGBoost

Abstract: Hypertension is a critical global health concern, necessitating accurate prediction models and effective prescription decisions to mitigate its risks. This study proposes a hybrid machine ...
Frontiers

Development and validation of an early predictive model for hemiplegic shoulder pain: a comparative study of logistic regression, support vector machine, and random forest

Objective: In this study, we aim to identify the predictive variables for hemiplegic shoulder pain (HSP) through machine learning algorithms, select the optimal model and predict the occurrence of HSP ...
GitHub

Issues: Joseph-Kobo/Machine-Learning---1.-Simple-Linear-Regression

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Issues are used to track todos, bugs, feature requests, and more.
Hosted on MSN

What Is Linear Regression In Machine Learning ? Understand With Examples

What is linear regression in machine learning ? Understanding Linear Regression in machine learning is considered as the basis or foundation in machine learning. In this video, we will learn what is ...
Hosted on MSN

Complete | What Is Linear Regression Machine Learning

This video is a one stop shop for understanding What is linear regression in machine learning. Linear regression in machine learning is considered as the basis or foundation in machine learning. This ...