Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty.
Lewis H. MervinMaria-Anna TrapotsiAvid M. AfzalIan P. BarrettAndreas BenderOla EngkvistPublished in: J. Cheminformatics (2021)
Keyphrases
- random forest
- decision trees
- random forests
- fold cross validation
- feature set
- cancer classification
- ensemble methods
- computer vision
- decision tree learning algorithms
- feature importance
- ensemble classifier
- support vector machine svm
- image classification
- classification accuracy
- feature selection
- benchmark datasets
- multi label
- text classification
- classification models
- generalization ability
- knowledge discovery
- feature space
- support vector
- data mining