Comparison of spectral clustering, K-clustering and hierarchical clustering on e-nose datasets: Application to the recognition of material freshness, adulteration levels and pretreatment approaches for tomato juices

Chemometrics and Intelligent Laboratory Systems

Volumn 133, Issue , 2014, Pages 17-24

  Hong, Xuezhen ^a   Wang, Jun ^a   Qi, Guande ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

Cluster validation; Electronic nose; Hierarchical cluster analysis; K clustering; Spectral clustering; Tomato juice

Indexed keywords

ADULTERATION DATASET; ARTICLE; CLUSTER ANALYSIS; CONTROLLED STUDY; DATA ANALYSIS; DATA BASE; ELECTRIC CONDUCTIVITY; ELECTRONIC NOSE; HIERARCHICAL CLUSTERING; K CLUSTERING; MATERIAL FRESHNESS DATASET; MATHEMATICAL COMPUTING; MEASUREMENT ACCURACY; PRIORITY JOURNAL; RAND INDEX; SPECTRAL CLUSTERING; STATISTICAL DISTRIBUTION; STATISTICAL MODEL; STATISTICAL PARAMETERS; STATISTICAL SIGNIFICANCE; TOMATO JUICE; VALIDATION PROCESS;

EID: 84896701506     PISSN: 01697439     EISSN: 18733239     Source Type: Journal    
DOI: 10.1016/j.chemolab.2014.01.017     Document Type: Article

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