期刊
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
卷 172, 期 -, 页码 33-42出版社
ELSEVIER
DOI: 10.1016/j.chemolab.2017.10.024
关键词
FTIR spectroscopy; Random forest; Software; Machine learning; Spectral diagnostics; Food testing
类别
资金
- EPSRC [EP/K000586/1]
- Scottish Enterprise
- EPSRC
- Dstl
- Rosemere Cancer Foundation
- Brain Tumour North West
- Sydney Driscoll Neuro-science Foundation
- EPSRC [EP/K000195/1, EP/K000586/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/K000586/1, EP/K000195/1] Funding Source: researchfish
PRFFECT is a computer program to aid with spectral preprocessing and the development of classification models. Via a simple text interface, PRFFECT allows users to select wavenumber ranges, perform spectral preprocessing, carry out data partitioning (into training and testing datasets), run a Random Forest classification, compute statistical results, and identify important descriptors for the classification. The preprocessing options provided fall into four categories: binning, smoothing, normalisation, and baseline correction. The program outputs a wide variety of useful data, including classification metrics and graphs showing the importance of individual wave numbers to the classification models. As proof-of-concept, PRFFECT has been benchmarked on preprocessing and classification of four food analysis datasets. Sensitivities and specificities above 0.92 were obtained in all cases. The results show that different preprocessing procedures are optimal for different datasets. The PRFFECT software is available freely to the community via GitHub. Link: https://github.com/Palmer-Lab/PRFFECT.
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