Performance evaluation of rotation forest for svm-based recursive feature elimination using hyperspectral imagery


Hyperspectral images provide important information for addressing complex classification problems required for a detailed characterization of spectral behavior of the target objects. Classification of such datasets into meaningful land use and land cover classes (LULC) has been the most concentrated topic in remote sensing arena. Rotation forest (RotFor), a… (More)
DOI: 10.1109/WHISPERS.2016.8071792

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