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Multiple SVMS based on random subspaces from kernel feature importance for hyperspectral image classification.
Cheng-Hsuan Li
Pei-Jyun Hsieh
Bor-Chen Kuo
Published in:
IGARSS (2017)
Keyphrases
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support vector
kernel function
feature importance
random subspaces
hyperspectral image classification
kernel methods
machine learning
feature selection
feature space
support vector machine
multi class
similarity measure
active learning
input space