Using unlabelled data to update classification rules with applications in food authenticity studies

By Nema Dean, Thomas Brendan Murphy, G. Downey. 2006

116 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Biomedical Engineering, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/fd36958e7318f4d47d48891307b75ec48868b2e6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Analytical Chemistry

1. D. Toher
2. Thomas Brendan Murphy
3. G. Downey
4. Paul David McNicholas

In Biomedical Engineering

1. D. Toher
2. Thomas Brendan Murphy
3. G. Downey

In Molecular Biology

1. D. Toher
2. Thomas Brendan Murphy
3. G. Downey
4. Paul David McNicholas

Citations in the corpus

• A comparison of model-based and regression classification techniques applied to near infrared spectroscopic data in food authentication studies (2007, methodology): “A recent extension of model-based classification that uses data with unknown group membership in the model-fitting procedure has been developed[ 5 ].”
• A mixture of generalized hyperbolic distributions (2013, background): “Model-based classification (e.g., Dean et al., 2006; McNicholas, 2010), or partial classification (cf. McLachlan, 1992, Section 2.7), can be regarded as a semi-supervised version of model-based clustering, while model-based discriminant analysis is supervised (cf. Hastie and Tibshirani, 1996).”