Jun 14, 2018 · We compare a One-Sided k-NN algorithm with two well-known binary classification algorithms, and conclude that the one-sided classifier is more robust to ...

This paper presents a new approach to classification of high dimensional spectroscopy data and demonstrates that it outperforms other current state-of-the art ...

Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, because they assume ...

Abstract. Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical per-.

Jun 14, 2018 · This paper presents a new approach to classification of high dimensional spectroscopy data and demonstrates that it outperforms other current ...

Aug 19, 2009 · Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, ...

Using the apparatus of statistical theory of detection, we develop the optimal classifier for spectroscopy data for a linear model of an echelle spectrograph ...

This paper presents a software package that allows chemists to analyze spectroscopy data using innovative machine learning (ML) techniques. Download Free PDF

The nature of the outliers (darker clusters) detected in the U-Matrix can vary: they can be instrumental errors, bad detections, or faint or unexpected objects.

This paper presents a new approach to classification of high dimensional spectroscopy data and demonstrates that it outperforms other current state-of-the art ...