Support Vector Machine Versus Random Forest for Remote Sensing Image Classification: A Meta-Analysis and Systematic Review.
Mohammadreza SheykhmousaMasoud MahdianPariHamid GhanbariFariba MohammadimaneshPedram GhamisiSaeid HomayouniPublished in: IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. (2020)
Keyphrases
- random forest
- meta analysis
- remote sensing
- systematic review
- image classification
- support vector machine
- svm classifier
- multi label
- remotely sensed data
- empirical studies
- decision trees
- multispectral
- change detection
- remote sensing images
- feature set
- multi class
- feature extraction
- microarray data
- image analysis
- machine learning
- image processing
- image fusion
- high resolution
- feature vectors
- fold cross validation
- feature selection
- land cover
- satellite images
- image features
- support vector
- support vector machine svm
- hyperspectral
- ensemble classifier
- remote sensing data
- ensemble methods
- training data
- gene expression profiles
- base classifiers
- feature space
- training set
- feature ranking
- k nearest neighbor
- kernel function
- knowledge discovery
- cluster analysis