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Clustering with position-specific constraints on variance: Applying redescending M-estimators to label-free LC-MS data analysis
BACKGROUND: Clustering is a widely applicable pattern recognition method for discovering groups of similar observations in data. While there are a large variety of clustering algorithms, very few of these can enforce constraints on the variation of attributes for data points included in a given clus...
Gorde:
| Egile Nagusiak: | , , |
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| Formatua: | Artigo |
| Hizkuntza: | Inglês |
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BioMed Central
2011
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| Gaiak: | |
| Sarrera elektronikoa: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3178548/ https://ncbi.nlm.nih.gov/pubmed/21884583 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/1471-2105-12-358 |
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