An efficient extraction-based Bagging ensemble for high-dimensional data classification.
Hsiao-Yun HuangYen-Chieh LiPublished in: SCIS&ISIS (2012)
Keyphrases
- high dimensional data
- high dimensionality
- regression problems
- dimension reduction
- dimensionality reduction
- training set
- nearest neighbor
- ensemble methods
- ensemble classification
- high dimensional
- imbalanced data
- low dimensional
- ensemble classifier
- majority voting
- decision trees
- subspace clustering
- decision tree classifiers
- classifier ensemble
- data points
- ensemble learning
- data analysis
- machine learning
- small sample size
- feature selection
- data sets
- pattern recognition
- input space
- classification accuracy
- high dimensional spaces
- linear discriminant analysis
- base classifiers
- high dimensional datasets
- random forest
- feature space
- similarity search
- manifold learning
- clustering high dimensional data
- base learners
- principal component analysis
- individual classifiers
- multivariate temporal data
- random forests
- feature extraction
- support vector machine
- support vector machine svm
- svm classifier
- machine learning methods
- weak classifiers
- classification algorithm
- nonlinear dimensionality reduction
- knn
- high dimensional data sets
- ensemble members
- benchmark datasets
- text classification
- active learning
- feature vectors
- data mining