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Spectrometric differentiation of yeast strains using minimum volume increase and minimum direction change clustering criteria.

Nuno FachadaMário A. T. FigueiredoVitor V. LopesRui Costa MartinsAgostinho C. Rosa
Published in: Pattern Recognit. Lett. (2014)
Keyphrases
  • minimum volume
  • clustering algorithm
  • k means
  • anomaly detection
  • outlier detection
  • data points
  • unsupervised learning
  • high dimensional data
  • distance metric
  • high throughput
  • density estimation