Predicting Financial Distress of Banks Using Random Subspace Ensembles of Support Vector Machines.
Petr HájekVladimír OlejRenáta MyskováPublished in: CSOC (1) (2015)
Keyphrases
- random subspace
- learning machines
- ensemble learning
- support vector
- random forest
- ensemble methods
- classifier fusion
- subspace methods
- financial distress
- random subspaces
- random sampling
- generalization ability
- early warning
- nearest neighbor classifiers
- linear discriminant analysis
- cross validation
- support vector machine
- majority voting
- svm classifier
- random forests
- base learners
- base classifiers
- decision trees
- feature subspace
- binary classification
- prediction accuracy
- classifier ensemble
- fusion scheme
- feature selection
- loss function
- active learning
- comparative analysis
- face recognition
- concept drift
- benchmark datasets
- classification accuracy
- logistic regression
- ensemble classifier
- puts forward
- fusion methods
- nearest neighbor
- financial information
- principal component analysis
- sample size