Least squares linear regression ... model and a procedure for calculation of uncertainties components of an analytical result due to sample preparation (uncertainty of weights and volumetric equipment ...

The binary target variable represented observed cognitive ... We trained and evaluated three predictive models—Random Forest, XGBoost, and Logistic Regression—using stratified cross-validation and ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector ...

Abstract: The recursive Gaussian process regression (RGPR ... Most of existing RGPR models are on the assumption that hyperparameters in the covariance function are fixed during the model calibration.

To achieve this goal, we develop a multivariate regression model of climate change, in which the change in a climate variable is represented by a linear combination of its sensitivity to CO2 forcing, ...

Abstract: This paper proposes a novel calibration method for linear array antennas based on the scattering signals of a standard metal cylinder. The method sequentially activates each element of the ...