Issue 9, 2019

Rapid classification of plastics by laser-induced breakdown spectroscopy (LIBS) coupled with partial least squares discrimination analysis based on variable importance (VI-PLS-DA)

Abstract

With the extensive use of plastic products, the recycling and reuse of plastics raise more concerns. Laser-induced breakdown spectroscopy (LIBS) and chemometric methods have been applied to classify plastics. However, the methods are prone to fall into over-fitting when predicting unknown samples. Variable importance is the impact of input variables to classification results. Selecting input variables by variable importance can be used to avoid over-fitting, which has been used for improving model performance based on random forest (RF). However, the progress of optimizing the parameters of RF model is complex. Partial least squares discrimination analysis (PLS-DA), most widely used in spectral data, is a simple and stable method in multivariate analysis. To avoid over-fitting phenomenon and acquire stable results, this paper presents an extension of PLS-DA that uses variable importance to select input variables, namely VI-PLS-DA. In order to validate the classification ability of VI-PLS-DA for plastics, VI-PLS-DA was compared with PLS-DA, RF, and VI-RF. VI-PLS-DA has the highest classification accuracy (99.55%) and shortest classification time (0.096 ms), which indicated a good classification performance for plastics analysis.

Graphical abstract: Rapid classification of plastics by laser-induced breakdown spectroscopy (LIBS) coupled with partial least squares discrimination analysis based on variable importance (VI-PLS-DA)

Article information

Article type
Paper
Submitted
18 Гру 2018
Accepted
31 Січ 2019
First published
31 Січ 2019

Anal. Methods, 2019,11, 1174-1179

Rapid classification of plastics by laser-induced breakdown spectroscopy (LIBS) coupled with partial least squares discrimination analysis based on variable importance (VI-PLS-DA)

K. Liu, D. Tian, H. Wang and G. Yang, Anal. Methods, 2019, 11, 1174 DOI: 10.1039/C8AY02755B

To request permission to reproduce material from this article, please go to the Copyright Clearance Center request page.

If you are an author contributing to an RSC publication, you do not need to request permission provided correct acknowledgement is given.

If you are the author of this article, you do not need to request permission to reproduce figures and diagrams provided correct acknowledgement is given. If you want to reproduce the whole article in a third-party publication (excluding your thesis/dissertation for which permission is not required) please go to the Copyright Clearance Center request page.

Read more about how to correctly acknowledge RSC content.

Social activity

Spotlight

Advertisements