query: Feature selection Stability of Elastic net vs Lasso
positive_passages.docid: 154377
positive_passages.text: What causes lasso to be unstable for feature selection?
negative_passages.docid: 88260
negative_passages.text: LASSO: Deriving the smallest lambda at which all coefficient are zero
negative_passages.docid: 95615
negative_passages.text: Equivalence between Elastic Net formulations
negative_passages.docid: 126797
negative_passages.text: Elasticity of log-log regression
negative_passages.docid: 126595
negative_passages.text: Does feature selection help improve the performance of machine learning?
negative_passages.docid: 158317
negative_passages.text: Understanding Lasso Regression's sparsity geometrically
negative_passages.docid: 144918
negative_passages.text: Lasso features selection through Crossvalidation
negative_passages.docid: 153341
negative_passages.text: Lasso regression feature selection
negative_passages.docid: 21979
negative_passages.text: Feature selection for "final" model when performing cross-validation in machine learning
negative_passages.docid: 110802
negative_passages.text: Model selection with low N?
negative_passages.docid: 115109
negative_passages.text: Euclidean distance is usually not good for sparse data (and more general case)?
negative_passages.docid: 149876
negative_passages.text: Dimensions of Scale (Gamma) and Offset (Beta) in Batch Norm
negative_passages.docid: 48892
negative_passages.text: whether to rescale indicator / binary / dummy predictors for LASSO
negative_passages.docid: 114625
negative_passages.text: Model selection and cross-validation: The right way
negative_passages.docid: 47453
negative_passages.text: Why will ridge regression not shrink some coefficients to zero like lasso?
negative_passages.docid: 3013
negative_passages.text: Why does the Lasso provide Variable Selection?
negative_passages.docid: 108556
negative_passages.text: Standardization vs. Normalization for Lasso/Ridge Regression