Matched-Pair Machine Learning

Matched-Pair Machine Learning

Following an analogous distinction in statistical hypothesis testing, and motivated by chemical plume detection in hyperspectral imagery, we investigate machine learning algorithms where the training set is comprised of matched pairs. We find that even conventional classifiers exhibit improved performance when the input data has a matched-pair structure, and we develop an example of a “dipole” ...

Transductive and Matched-Pair Machine Learning for Difficult Target Detection Problems

This paper will describe the application of two non-traditional kinds of machine learning (transductive machine learning and the more recently proposed matched-pair machine learning) to the target detection problem. The approach combines explicit domain knowledge to model the target signal with a more agnostic machine-learning approach to characterize the background. The concept is illustrated ...

Matched Peptides: Tuning Matched Molecular Pair Analysis for Biopharmaceutical Applications

Biopharmaceuticals hold great promise for the future of drug discovery. Nevertheless, rational drug design strategies are mainly focused on the discovery of small synthetic molecules. Herein we present matched peptides, an innovative analysis technique for biological data related to peptide and protein sequences. It represents an extension of matched molecular pair analysis toward macromolecula...

Matched-Pair Studies with Misclassified Ordinal Data

Machine learning algorithms in air quality modeling

Modern studies in the field of environment science and engineering show that deterministic models struggle to capture the relationship between the concentration of atmospheric pollutants and their emission sources. The recent advances in statistical modeling based on machine learning approaches have emerged as solution to tackle these issues. It is a fact that, input variable type largely affec...