Investigating the impact of classification features and classifiers on crop mapping performance in heterogeneous agricultural landscapes.
Huanxue ZhangYuji WangJiali ShangMingxu LiuQiangzi LiPublished in: Int. J. Appl. Earth Obs. Geoinformation (2021)
Keyphrases
- feature set
- svm classifier
- classification models
- classification method
- extracted features
- classification process
- classification accuracy
- class labels
- feature vectors
- feature extraction
- classification algorithm
- decision trees
- support vector machine classifiers
- feature space
- feature selection algorithms
- decision tree classifiers
- feature subset
- feature selection
- machine learning approaches
- classification systems
- classification decisions
- multiple classifiers
- support vector
- bayes classifier
- training set
- ensemble classifier
- feature weights
- feature reduction
- supervised classification
- final classification
- naive bayes
- feature values
- bayesian classifier
- input features
- machine learning methods
- roc curve
- classification performances
- support vector machine
- multiple features
- weak classifiers
- benchmark datasets
- individual classifiers
- training data
- accurate classification
- linear svm
- individual features
- naive bayes classifier
- supervised classifiers
- classification schemes
- probabilistic classifiers
- classifier combination
- classification rate
- text classification
- support vector machine svm
- machine learning
- k nearest neighbour
- feature ranking
- sufficient training data
- discriminative classifiers
- multiclass classification
- accurate classifiers
- machine learning algorithms
- supervised learning
- support vector machine classifier
- highest accuracy
- train a support vector machine
- training examples
- rule based classifier
- boosted classifiers
- sequential forward selection
- image classification
- highly discriminative
- svm classification
- kernel function
- classifier ensemble
- supervised learning algorithms
- majority voting