Addendum: Regularization and variable selection via the elastic net
Explore this paper's citation graph
Summary
The piecewise linearity of the lasso solution path was first proved by Osborne et al. (2000), who also described an efficient algorithm for calculating the complete lasso solutions path.
- Type
- article
- Published
- 2005-11-01
- Cited by
- 11,036
- References
- 2
- Access
- Open access
- OpenAlex
- https://openalex.org/W1993273815
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:14134075
Keywords
Addendum, Elastic net regularization, Regularization (linguistics), Variable (mathematics), Mathematics
References
Cited by
- Regularization methods for prediction in dynamic graphs and e-marketing applications
- Penalized Least Squares Regression Methods and Applications to Neuroimaging
- Support Vector Machines With Constraints for Sparsity in the Primal Parameters
- Optimized application of penalized regression methods to diverse genomic data
- Joint-Structured-Sparsity-Based Classification for Multiple-Measurement Transient Acoustic Signals
- Genomic selection using regularized linear regression models: ridge regression, lasso, elastic net and their extensions
- Predicting evolutionary responses to selection on polyandry in the wild: additive genetic covariances with female extra-pair reproduction
- Decoding the memorization of individual stimuli with direct human brain recordings
- Comparison of neuroimaging modalities for the prediction of conversion from mild cognitive impairment to Alzheimer's dementia.
- Quantifying human sensitivity to spatio-temporal information in dynamic faces.
- Feature Screening via Distance Correlation Learning
- Multilinear Sparse Principal Component Analysis
- Prediction of brain maturity based on cortical thickness at different spatial resolutions
- Chlamydia caviae infection alters abundance but not composition of the guinea pig vaginal microbiota
- Blood-based lung cancer biomarkers identified through proteomic discovery in cancer tissues, cell lines and conditioned medium
- Integration of Sparse Multi-modality Representation and Geometrical Constraint for Isointense Infant Brain Segmentation
- Brain size predicts problem-solving ability in mammalian carnivores
- Learning statistical models of phenotypes using noisy labeled training data
- Pathway-based approach using hierarchical components of collapsed rare variants
- Incorporating Functional Annotations for Fine-Mapping Causal Variants in a Bayesian Framework Using Summary Statistics
Related papers
- Comparison of Feature Selection Methods Based on Lasso
- A Two-Step Feature Selection Procedure to Handle High-Dimensional Data in Regression Problems
- Cluster feature selection in high-dimensional linear models
- Ensemble Feature Selection Methods for a Better Regularization of the Lasso Estimate in P >> N Gene Expression Datasets
- The elastic behavior of entropic "fisherman's net”
- Predictive Systems: Role of Feature Selection in Prediction of Heart Disease