Abstract: We consider the shuffled linear regression problem where the correspondences between covariates and responses are unknown. While the existing formulation assumes an ideal underlying ...

Abstract: For a relatively small labeled dataset from high-dimensional generalized linear models with block-wise missing covariates and a large unlabeled dataset, we utilize a model-assisted approach ...

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, ...

Chemical Sciences Division, National Institute of Standards and Technology, Gaithersburg, Maryland 20899-8320, United States ...

State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China ...

1 Department of Plant Pathology, The Ohio State University, Wooster, OH, United States 2 Center for Integrated Fungal Research, Department of Entomology and Plant Pathology, North Carolina State ...

Generalized Linear Regression Model (GLM) and Graph Embedding (GE) - Park-Sung-Joon/GLMGE ...

This paper critically examines ‘kitchen sink regression’, a practice characterised by the manual or automated selection of variables for a multivariable regression model based on p values or ...