Ligand-based drug design combines AI and QSAR modeling to prioritize drug candidates, minimizing preclinical failures and ...

The goal of liu.lab4.algorithms is to provide an R implementation of a multiple linear regression mode. This package was created for Lab 4 in the course 732A94 Advanced R Programming at Linköping ...

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 ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is the simplest machine learning technique to predict a single numeric value, ...

As one of the important statistical methods, quantile regression (QR) extends traditional regression analysis. In QR, various quantiles of the response variable are modeled as linear functions of the ...

Abstract: This study focuses on the AHET Dataset, aiming to explore and optimize forecasting methods by combining two predictive models-ARIMA (AutoRegressive Integrated Moving Average) and GBDT ...

Abstract: This paper presents an autoML algorithm to select linear regression model and its performance evaluation for any linear dataset. It computes and compares the performance of various multiple ...

This study introduces an XGBoost-MICE (Multiple Imputation by Chained Equations) method for addressing missing data in mine ventilation parameters. Using historical ventilation system data from ...

ABSTRACT: This paper investigates the relationship between GDP growth and imports from high income economies, low-to-medium income economies and the Arab World for 15 European Union countries having a ...