Utilizing an ensemble of SVMs with GMM voting-based mechanism in predicting dangerous seismic events in active coal mines.
Lukasz PodlodowskiPublished in: FedCSIS (2016)
Keyphrases
- majority voting
- support vector
- gaussian mixture model
- ensemble methods
- feature selection
- weighted voting
- training data
- event detection
- training set
- multi class
- voting schemes
- knn
- dangerous situations
- feature vectors
- seismic data
- base classifiers
- ensemble learning
- machine learning
- generalization ability
- feature ranking
- voting scheme
- classifier ensemble
- regression problems
- support vector machine svm
- imbalanced data
- kernel function
- pattern mining
- gaussian mixture modeling
- binary classification
- random forests
- random forest
- support vector machine
- learning algorithm
- prediction accuracy
- training samples
- accurate classifiers
- em algorithm
- feature space
- decision trees