Systematic Investigation of Error Distribution in Machine Learning Algorithms Applied to the Quantum-Chemistry QM9 Data Set Using the Bias and Variance Decomposition.
Luis Cesar de AzevedoGabriel A. PinheiroMarcos G. QuilesJuarez L. F. Da SilvaRonaldo C. PratiPublished in: J. Chem. Inf. Model. (2021)
Keyphrases
- machine learning algorithms
- benchmark data sets
- data sets
- learning algorithm
- learning problems
- machine learning methods
- machine learning
- predictive accuracy
- random forests
- learning tasks
- low variance
- bias variance decomposition
- variance reduction
- real world
- decision trees
- machine learning approaches
- prediction error
- machine learning models
- data mining
- transfer learning
- pairwise
- training data
- training and test data