Trade-off between bagging and boosting for quantum separability-entanglement classification.
Sanuja D. MohantyRam Narayan PatroPradyut Kumar BiswalBiswajit PradhanSk SazimPublished in: Quantum Inf. Process. (2024)
Keyphrases
- trade off
- ensemble classification
- decision trees
- machine learning
- ensemble learning
- ensemble methods
- ensemble classifier
- majority voting
- training set
- base classifiers
- weak classifiers
- randomized trees
- pattern recognition
- learning algorithm
- classification algorithm
- base learners
- class labels
- benchmark datasets
- support vector
- classification models
- classification accuracy
- feature selection
- gradient boosting
- weak learners
- feature vectors
- support vector machine
- machine learning methods
- imbalanced data
- svm classifier
- cross validation
- tree induction
- generalization ability
- dimensionality reduction
- random forests
- supervised learning
- image classification
- regression problems
- multiple classifier systems
- variance reduction
- accurate classifiers
- decision tree classifiers
- class separability
- feature extraction
- random forest
- meta learning