Explainable Matrix - Visualization for Global and Local Interpretability of Random Forest Classification Ensembles.
Mário Popolin NetoFernando V. PaulovichPublished in: CoRR (2020)
Keyphrases
- random forest
- decision trees
- random subspace
- random forests
- ensemble methods
- fold cross validation
- ensemble classifier
- feature set
- cancer classification
- rotation forest
- ensemble learning
- base classifiers
- imbalanced data
- feature ranking
- decision tree learning algorithms
- feature importance
- machine learning methods
- prediction accuracy
- image classification
- training set
- machine learning
- generalization ability
- classification accuracy
- feature extraction
- logistic regression
- classification models
- support vector machine svm
- training samples
- feature vectors
- feature selection
- feature space
- benchmark datasets
- classification algorithm
- class labels
- base learners
- support vector machine
- majority voting
- unsupervised learning
- classifier combination
- individual classifiers
- image processing
- test set