Abstract: 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 ...
ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...
ABSTRACT: Ordinal outcome neural networks represent an innovative and robust methodology for analyzing high-dimensional health data characterized by ordinal outcomes. This study offers a comparative ...
Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
A machine learning random forest regression system predicts a single numeric value. A random forest is an ensemble (collection) of simple decision tree regressors that have been trained on different ...
Background: Frailty is common in atrial fibrillation (AF) patients, but the specific risk factors contributing to frailty need further investigation. There is an urgent need for a risk prediction ...
Multicenter electronic health records can support quality improvement and comparative effectiveness research in stroke. However, limitations of electronic health record–based research include ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback