Learn how to detect, handle, and evaluate outliers in your linear regression model. Find out how outliers affect the fit, accuracy, and reliability of your model.

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression using JavaScript. Linear regression is ...

Objective Long-term azithromycin treatment effectively prevents acute exacerbations of chronic obstructive pulmonary disease ...

Optimally managing these resources depends on predicting water availability. We built a probabilistic nonlinear regression water supply forecast (WSF) technique for the US Department of Agriculture, ...

In this paper, we consider the feature ranking problem, where, given a set of training instances, the task is to associate a score with the features in order to assess their relevance. Feature ranking ...

Cosmic map: a thousand-colour image of the Sculptor Galaxy captured with the MUSE instrument at ESO’s Very Large Telescope. (Courtesy: ESO/E Congiu et al.) Astronomers at the European Southern ...

A longitudinal, deep learning approach reveals challenges and opportunities in establishing brain age as an effective metric of aging, with particular consideration given to underrepresented ...

Following the methodology of Pinheiro and Bates (1998) and recently used by Mehtätalo et al. (2015) and Corral-Rivas et al. (2019), the non-linear mixed-effect was defined as [34], where hij is the ...

This plot shows the relationship between two variables, with a fitted regression line and a shaded confidence interval. The equation and p-value indicate the strength and significance of the ...

Computationally efficient Bayesian variable selection method to identify linear and nonlinear effects in regression models where a predictor (or feature) can have a zero effect, a non-zero linear ...