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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 ...
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 ...