The simplicity of XGBoost algorithm versus the complexity of Random Forest, Support Vector Machine, and Neural Networks algorithms in urban forest classification.
Fatwa RamdaniMuhammad Tanzil FurqonPublished in: F1000Research (2022)
Keyphrases
- random forest
- classification algorithm
- decision tree learning algorithms
- support vector machine
- learning algorithm
- neural network
- decision trees
- optimization algorithm
- ensemble classifier
- random forests
- classification method
- benchmark datasets
- support vector
- support vector machine svm
- machine learning algorithms
- feature vectors
- multi class
- decision tree learning algorithm
- feature reduction
- fold cross validation
- machine learning methods
- svm classifier
- training set
- active learning
- generalization ability
- ensemble methods
- text classification
- classification accuracy
- feature space
- text categorization
- computer vision
- k nearest neighbor
- feature selection algorithms
- image classification
- markov random field
- feature set
- dimensionality reduction
- nearest neighbor