Now showing items 1-5 of 5
A Machine Learning Application for Classification of Chemical Spectra
This paper presents a software package that allows chemists to analyze spectroscopy data using innovative machine learning (ML) techniques. The package, designed for use in conjunction with lab-based spectroscopic ...
The Effect of Principal Component Analysis on Machine Learning Accuracy with High Dimensional Spectral Data
The classi¿cation of high dimensional data, such as images, gene-expression data and spectral data, poses an interesting challenge to machine learning, as the presence of high numbers of redundant or highly correlated ...
Qualitative and Quantitative Analysis of Chlorinated Solvents using Raman Spectroscopy and Machine Learning
The unambiguous identification and quantification of hazardous materials is of increasing importance in many sectors such as waste disposal, pharmaceutical manufacturing, and environmental protection. One particular ...
Multi-Class and Single-Class Classification Approaches to Vehicle Model Recognition from Images
This paper investigates the use of machine learning classification techniques applied to the task of recognising the make and model of vehicles. Although a number of vehicle classification systems already exist, most of ...
An evolutionary approach to automatic kernel construction
Abstract. Kernel-based learning presents a unified approach to machine learning problems such as classification and regression. The selection of a kernel and associated parameters is a critical step in the application of ...