Using Bayesian Optimization to Effectively Tune Random Forest and XGBoost Hyperparameters for Early Alzheimer's Disease Diagnosis.
Louise BlochChristoph M. FriedrichPublished in: MobiHealth (2020)
Keyphrases
- random forest
- disease diagnosis
- hyperparameters
- bayesian inference
- maximum likelihood
- decision trees
- model selection
- cross validation
- closed form
- feature set
- random sampling
- early diagnosis
- maximum a posteriori
- bayesian framework
- ensemble methods
- support vector
- sample size
- prior information
- em algorithm
- incremental learning
- missing values
- noise level
- learning algorithm
- comparative analysis
- incomplete data
- pairwise
- multi label
- logistic regression
- feature vectors
- computer aided diagnosis
- fold cross validation
- prior knowledge
- text classification