query: Challenges in interpretation of variable selection from LASSO and OLS
positive_passages.docid: 142784
positive_passages.text: For linear classifiers, do larger coefficients imply more important features?
negative_passages.docid: 11427
negative_passages.text: Using regularization when doing statistical inference
negative_passages.docid: 31175
negative_passages.text: Interpretation of betas when there are multiple categorical variables
negative_passages.docid: 97758
negative_passages.text: Is using correlation matrix to select predictors for regression correct?
negative_passages.docid: 144918
negative_passages.text: Lasso features selection through Crossvalidation
negative_passages.docid: 138225
negative_passages.text: Nested cross validation for model selection
negative_passages.docid: 65293
negative_passages.text: Dealing with Categorical variables in Multiple Regression
negative_passages.docid: 142875
negative_passages.text: Moderated regression: Why do we calculate a *product* term between the predictors?
negative_passages.docid: 113046
negative_passages.text: Coefficients and significance of lasso/ridge
negative_passages.docid: 123794
negative_passages.text: Interpretation of LASSO regression coefficients
negative_passages.docid: 69307
negative_passages.text: Interpretting LASSO variable trace plots
negative_passages.docid: 80644
negative_passages.text: Finding the unbiased variance estimator in high dimensional spaces
negative_passages.docid: 45291
negative_passages.text: Overmatching bias and confounding variables
negative_passages.docid: 44881
negative_passages.text: Using lasso for feature selection, followed by a non-regularized regression
negative_passages.docid: 55662
negative_passages.text: How to use principal components analysis to select variables for regression?
negative_passages.docid: 48892
negative_passages.text: whether to rescale indicator / binary / dummy predictors for LASSO
negative_passages.docid: 154377
negative_passages.text: What causes lasso to be unstable for feature selection?