Abstract: Higher education decision-making is greatly improved by machine learning (ML), especially when it comes to forecasting student placements that affect career prospects or an institution's ...

Linear regression is the most fundamental machine learning technique to create a model that predicts a single numeric value. One of the three most common techniques to train a linear regression model ...

Quadratic regression extends linear regression by adding squared terms and pairwise interaction terms, enabling the model to capture non-linear structure and predictor interactions. The article ...

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 ...

The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...

Across the literature, multivariable models for predicting giant cell arteritis diagnoses showed various methodological weaknesses. Multivariable models can aid in the diagnosis of giant cell ...

Department of Hepatobiliary Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, China Objective: Compare the performance of the Multivariable logistic ...

ABSTRACT: There is a set of points in the plane whose elements correspond to the observations that are used to generate a simple least-squares regression line. Each value of the independent variable ...

Abstract: This study combined linear discriminant analysis (LDA) and multivariate logistic regression models to systematically analyze key indicators in flood prediction, aiming to identify factors ...