RUESVMs: An Ensemble Method to Handle the Class Imbalance Problem in Land Cover Mapping Using Google Earth Engine.
Amin NabourehHamid EbrahimyMohsen AzadbakhtJinhu BianMeisam AmaniPublished in: Remote. Sens. (2020)
Keyphrases
- class imbalance
- ensemble methods
- land cover
- satellite images
- remote sensing
- class distribution
- base classifiers
- change detection
- multispectral
- prediction accuracy
- active learning
- cost sensitive
- concept drift
- ensemble learning
- remote sensing images
- decision trees
- benchmark datasets
- random forest
- machine learning methods
- supervised classification
- satellite imagery
- geographic information systems
- feature selection
- image processing
- feature subset
- multi class
- high resolution
- image analysis
- training set
- training data
- base learners
- data sets
- naive bayes
- image data
- high dimensional
- database systems
- urban areas