Using information gain to build meaningful decision forests for multilabel classification.
Kevin GoldAllison PetrosinoPublished in: ICDL (2010)
Keyphrases
- information gain
- multilabel classification
- decision forest
- decision trees
- text categorization
- ensemble methods
- logistic regression
- multi label
- instance based learning
- random forests
- naive bayes
- feature selection
- rule induction
- random forest
- lazy learning
- machine learning algorithms
- mutual information
- text classification
- base classifiers
- training set
- machine learning
- classification rules
- semi supervised learning
- nearest neighbor
- training data
- data sets
- k nearest neighbor
- correlation coefficient
- decision rules
- knn