Sensitivity of support vector machines to random feature selection in classification of hyperspectral data

IEEE Transactions on Geoscience and Remote Sensing

Volumn 48, Issue 7, 2010, Pages 2880-2889

  Waske, Björn ^a   Van Der Linden, Sebastian ^c   Benediktsson, Jón Atli ^b   Rabe, Andreas ^c   Hostert, Patrick ^c  

^a UNIVERSITY OF BONN   (Germany)

^b HUMBOLDT UNIVERSITY   (Germany)

^c UNIVERSITY OF ICELAND   (Iceland)

Author keywords

Classifier ensembles; Hyperspectral data; Multiple classifier systems (MCSs); Random feature selection (RFS); Support vector machines (SVMs)

Indexed keywords

CLASSIFIER ENSEMBLES; FEATURE SELECTION; HYPERSPECTRAL DATA; MULTIPLE CLASSIFIER SYSTEMS; RANDOM FEATURE SELECTION (RFS);

CLASSIFICATION (OF INFORMATION); CLASSIFIERS; DECISION TREES; EXPERIMENTS; FEATURE EXTRACTION; LANDFORMS; LEARNING ALGORITHMS; REMOTE SENSING; VECTORS;

SUPPORT VECTOR MACHINES;

ACCURACY ASSESSMENT; ALGORITHM; DATA SET; FOREST ECOSYSTEM; IMAGE CLASSIFICATION; LAND COVER; REMOTE SENSING; SENSITIVITY ANALYSIS; SPECTRAL ANALYSIS; STATISTICAL DATA; VECTOR;

EID: 77953871614     PISSN: 01962892     EISSN: None     Source Type: Journal    
DOI: 10.1109/TGRS.2010.2041784     Document Type: Article

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