In this paper, we focus on the problem of polynomial regression with uncertain polynomial order and coefficients. For polynomial regression problem, a probabilistic graph model with polynomial ...

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

ABSTRACT: In this work, we seek the relationship between the order of the polynomial model and the number of knots and intervals that we need to fit the splines regression model. Regression models ...

ABSTRACT: In this work, we seek the relationship between the order of the polynomial model and the number of knots and intervals that we need to fit the splines regression model. Regression models ...

A comprehensive model was developed utilizing mass transfer and machine learning (ML). In the machine learning section, three distinct regression models, namely, Decision Tree Regression (DTR), ...

It is faster and more electricity-saving to obtain the efficiency through a prediction model compared with the experimental methods. In this work, a dehumidification efficiency prediction model based ...

2 Amsterdam Public Health, Methodology, Amsterdam, Netherlands Objective: Traditional methods to deal with non-linearity in regression analysis often result in loss of information or compromised ...