Abstract: Flood prediction as we known is a important role in reducing the impacts of effective disasters . This paper says that a linear regression-based model is designed for forecasting flood ...

Commonly used linear regression focuses only on the effect on the mean value of the dependent variable and may not be useful in situations where relationships across the distribution are of interest.

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Standard linear regression predicts a single numeric value ...

School of Computing and Engineering, University of West, London, UK. In recent years, inflation has been a worrying factor for every country, which has become particularly high due to various ...

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict an employee's salary based on age, height, high school grade point ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

1 Departments of Computer Sciences, Nasarawa State University, Keffi, Nigeria. 2 Departments of Computer Sciences, University of Jos, Jos, Nigeria. Due to the rapid development of logistic industry, ...

Abstract: For more precise results, of earthquake predictions given by the KNN algorithm, this research employs the Linear Regression Algorithm. This research makes use of both the KNN algorithm and ...

To address the limitations of commonly used cross-validation methods, the linear regression method (LR) was proposed to estimate population accuracy of predictions based on the implicit assumption ...