Now showing items 1-5 of 5
Classification of a Target Analyte in Solid Mixtures using Principal Component Analysis, Support Vector Machines and Raman Spectroscopy
The quantitative analysis of illicit materials using Raman spectroscopy is of widespread interest for law enforcement and healthcare applications. One of the difficulties faced when analysing illicit mixtures is the ...
One-Class Support Vector Machine Calibration Using Particle Swarm Optimisation
Abstract. Population-based search methods such as evolutionary algorithms, shuffled complex algorithms, simulated annealing and ant colony search are increasingly used as automatic calibration methods ...
Analysis of the Effects of Unexpected Outliers in the Classification of Spectroscopy Data
Multi-class classification algorithms are very widely used, but we argue that they are not always ideal from a theoretical perspective, because they assume all classes are characterised by the data, whereas in many ...
The Genetic Evolution of Kernels for Support Vector Machine Classifiers
Abstract. The Support Vector Machine (SVM) has emerged in recent years as a popular approach to the classi¿cation of data. One problem that faces the user of an SVM is how to choose a kernel and the speci¿c parameters for ...
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 ...