Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using pseudo-inverse training. Compared to other training techniques, such as stochastic gradient descent, ...
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 ...
Abstract: The purpose of this work is to improve the detection of fraud websites using Novel Linear Regression Algorithm and Recurrent Neural Network Algorithm. Materials and Methods: Novel Linear ...
This C library provides efficient implementations of linear regression algorithms, including support for stochastic gradient descent (SGD) and data normalization techniques. It is designed for easy ...
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: Burundi faces major agricultural constraints, including land fragmentation, soil erosion, limited access to inputs, inadequate infrastructure and demographic pressures that exacerbate food ...
ABSTRACT: Continuous groundwater quality monitoring poses significant challenges affecting the environment and public health. Groundwater in Abidjan, specifically from the Continental Terminal (CT), ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results