Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
ABSTRACT: The solar data used to size installations for energy needs are most often oversized. The data used are either old or suffer from the effects of climate change or from data extrapolated to a ...
Abstract: Mixed linear regression (MLR) models nonlinear data as a mixture of linear components. When noise is Gaussian, the Expectation-Maximization (EM) algorithm is commonly used for maximum ...
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 ...
ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...
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, ...
In this video, we will implement Multiple Linear Regression in Python from Scratch on a Real World House Price dataset. We will not use built-in model, but we will make our own model. This can be a ...
Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of linear regression with two-way interactions between predictor variables. Compared to standard linear ...
1 Shangwan Coal Mine, Ejin Horo Banner, Ordos, China 2 CCTEG Xi’an Research Institute Co. Ltd., Xi’an, China This study introduces an XGBoost-MICE (Multiple Imputation by Chained Equations) method for ...
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