To minimise the potential for inferential bias, we conducted multiple imputation ... using a Schoenfeld residuals plot,25 and we found no violation of the assumption in this study. In addition to ...

A novel self-commissioning identification procedure is introduced, adopting multiple linear regression. The technique is tested on a commercial drive in comparison with state-of-the-art techniques. In ...

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. One crucial but often overlooked aspect is the ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

Abstract: We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a ...

Piece-wise non-linear regression is a long-standing problem in the machine learning domain that has long plagued machine learning researchers. It is extremely difficult for users to determine the ...

Implementing binary / multiple logistic regression models, for the well known mnist dataset while also creating the support vector machine(SVM) models ...