Bias and variance residuals for machine learning nonlinear simplex regressions.
Patrícia L. EspinheiraLuana C. M. SilvaFrancisco Cribari-NetoPublished in: Expert Syst. Appl. (2021)
Keyphrases
- machine learning
- low variance
- variance reduction
- bias variance analysis
- bias variance decomposition
- machine learning methods
- reinforcement learning
- pattern recognition
- least squares
- text mining
- machine learning algorithms
- real valued
- knowledge acquisition
- linear programming
- feature selection
- learning algorithm
- explanation based learning
- supervised learning
- text classification
- model selection
- computer science
- inductive learning
- simplex method
- correlation coefficient
- learning tasks
- semi supervised learning
- sample size
- neural network
- decision trees
- computer vision
- statistical methods
- kernel methods
- learning problems
- naive bayes
- inductive logic programming
- denoising
- machine learning approaches
- natural language processing
- knowledge representation
- active learning
- inductive bias
- data mining