Exploiting random projections and sparsity with random forests and gradient boosting methods - Application to multi-label and multi-output learning, random forest model compression and leveraging input sparsity.
Arnaud JolyPublished in: CoRR (2017)
Keyphrases
- random forest
- random forests
- multi label
- learning tasks
- decision trees
- base learners
- feature set
- learning algorithm
- cross validation
- image classification
- graph cuts
- sparse representation
- text categorization
- prior knowledge
- machine learning algorithms
- neural network
- supervised learning
- learning process
- high dimensional
- random sampling
- reinforcement learning
- learning scheme
- data mining