Learning a Spatial Ensemble of Classifiers for Raster Classification: A Summary of Results.
Zhe JiangShashi ShekharAzamat KamzinJoseph F. KnightPublished in: ICDM Workshops (2014)
Keyphrases
- training set
- supervised learning
- multi category
- learning algorithm
- decision trees
- feature selection
- training data
- support vector
- final classification
- classifier ensemble
- classification method
- ensemble learning
- supervised classification
- class labels
- learning tasks
- machine learning algorithms
- base learners
- machine learning methods
- svm classifier
- multiclass classification
- weak learners
- training samples
- classification accuracy
- unsupervised learning
- support vector machine
- neural network
- bayesian network classifiers
- majority voting
- feature vectors
- ensemble classifier
- decision boundary
- classification systems
- multiple classifiers
- classification models
- multiple classifier systems
- combining classifiers
- classification algorithm
- positive and unlabeled examples
- concept drifting data streams
- accurate classifiers
- imbalanced data
- co training
- ensemble methods
- spatial data
- binary images
- benchmark datasets
- image classification
- feature space
- machine learning