Class imbalance: A crucial factor affecting the performance of tea plantations mapping by machine learning.
Yuanjun XiaoJingfeng HuangWei WengRan HuangQi ShaoChang ZhouShengcheng LiPublished in: Int. J. Appl. Earth Obs. Geoinformation (2024)
Keyphrases
- class imbalance
- machine learning
- active learning
- cost sensitive learning
- class distribution
- cost sensitive
- feature selection
- small disjuncts
- majority class
- sampling methods
- machine learning methods
- imbalanced data
- high dimensionality
- software defect prediction
- imbalanced datasets
- minority class
- pattern recognition
- data mining
- concept drift
- learning tasks
- learning algorithm
- decision trees
- information extraction
- data sets
- reinforcement learning
- unsupervised learning
- support vector machine
- data analysis
- unlabeled data
- learning models
- k nearest neighbor
- error prone
- semi supervised learning
- benchmark datasets