Optimizing Ensemble Weights and Hyperparameters of Machine Learning Models for Regression Problems.
Mohsen ShahhosseiniGuiping HuHieu PhamPublished in: CoRR (2019)
Keyphrases
- regression problems
- hyperparameters
- cross validation
- model selection
- bayesian inference
- closed form
- bayesian framework
- support vector
- random sampling
- prior information
- noise level
- maximum likelihood
- sample size
- em algorithm
- incremental learning
- maximum a posteriori
- incomplete data
- missing values
- parameter space
- genetic programming
- parameter settings
- generative model
- learning models
- machine learning
- machine learning algorithms
- probabilistic model
- prior knowledge
- training set
- neural network
- class labels
- regression model
- supervised learning
- upper bound
- ensemble methods
- active learning
- artificial neural networks
- feature space
- feature selection