Robust variable selection in the framework of classification with label noise and outliers: Applications to spectroscopic data in agri-food
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Robust variable selection in the framework of classification with label noise and outliers: Applications to spectroscopic data in agri-food
Authors
Keywords
Variable selection, Robust classification, Label noise, Outlier detection, Near infrared spectroscopy, Mid infrared spectroscopy, Agri-food
Journal
ANALYTICA CHIMICA ACTA
Volume 1153, Issue -, Pages 338245
Publisher
Elsevier BV
Online
2021-02-01
DOI
10.1016/j.aca.2021.338245
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Rapid Identification and Visualization of Jowl Meat Adulteration in Pork Using Hyperspectral Imaging
- (2020) Hongzhe Jiang et al. Foods
- Untargeted identification of adulterated Sanqi powder by near-infrared spectroscopy and one-class model
- (2020) Hui Chen et al. JOURNAL OF FOOD COMPOSITION AND ANALYSIS
- A robust approach to model-based classification based on trimming and constraints
- (2019) Andrea Cappozzo et al. Advances in Data Analysis and Classification
- Quantitative analysis of yeast fermentation process using Raman spectroscopy: Comparison of CARS and VCPA for variable selection
- (2019) Hui Jiang et al. SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
- Prediction of holocellulose and lignin content of pulp wood feedstock using near infrared spectroscopy and variable selection
- (2019) Long Liang et al. SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
- Rejoinder to the discussion of “The power of monitoring: how to make the most of a contaminated multivariate sample”
- (2018) Andrea Cerioli et al. Statistical Methods and Applications
- Efficient robust methods via monitoring for clustering and multivariate data analysis
- (2018) Marco Riani et al. PATTERN RECOGNITION
- A reweighting approach to robust clustering
- (2017) Francesco Dotto et al. STATISTICS AND COMPUTING
- Bayesian nonparametric classification for spectroscopy data
- (2014) Luis Gutiérrez et al. COMPUTATIONAL STATISTICS & DATA ANALYSIS
- Determination of soil properties with visible to near- and mid-infrared spectroscopy: Effects of spectral variable selection
- (2014) M. Vohland et al. GEODERMA
- Classification in the Presence of Label Noise: A Survey
- (2014) Benoit Frenay et al. IEEE Transactions on Neural Networks and Learning Systems
- Simultaneous data pre-processing and SVM classification model selection based on a parallel genetic algorithm applied to spectroscopic data of olive oils
- (2013) Olivier Devos et al. FOOD CHEMISTRY
- Probabilistic model-based discriminant analysis and clustering methods in chemometrics
- (2013) Charles Bouveyron JOURNAL OF CHEMOMETRICS
- Recursive weighted partial least squares (rPLS): an efficient variable selection method using PLS
- (2013) Åsmund Rinnan et al. JOURNAL OF CHEMOMETRICS
- The Generalized Pairs Plot
- (2013) John W. Emerson et al. JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
- Variable selection in model-based discriminant analysis
- (2011) C. Maugis et al. JOURNAL OF MULTIVARIATE ANALYSIS
- Variables selection methods in near-infrared spectroscopy
- (2010) Zou Xiaobo et al. ANALYTICA CHIMICA ACTA
- Variable selection and updating in model-based discriminant analysis for high dimensional data with food authenticity applications
- (2010) Thomas Brendan Murphy et al. Annals of Applied Statistics
- Gaussian mixture models for the classification of high-dimensional vibrational spectroscopy data
- (2010) Julien Jacques et al. JOURNAL OF CHEMOMETRICS
- Sparse Partial Least Squares Classification for High Dimensional Data
- (2010) Dongjun Chung et al. Statistical Applications in Genetics and Molecular Biology
- Exploring the number of groups in robust model-based clustering
- (2010) L. A. García-Escudero et al. STATISTICS AND COMPUTING
- Key wavelengths screening using competitive adaptive reweighted sampling method for multivariate calibration
- (2009) Hongdong Li et al. ANALYTICA CHIMICA ACTA
- Confirmation of Food Origin Claims by Fourier Transform Infrared Spectroscopy and Chemometrics: Extra Virgin Olive Oil from Liguria
- (2009) Siobhán Hennessy et al. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY
- Kernel methods in machine learning
- (2008) Thomas Hofmann et al. ANNALS OF STATISTICS
- Biomarker discovery in mass spectral profiles by means of selectivity ratio plot
- (2008) Tarja Rajalahti et al. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
- A variable selection method based on uninformative variable elimination for multivariate calibration of near-infrared spectra
- (2007) Wensheng Cai et al. CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationBecome a Peeref-certified reviewer
The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.
Get Started