Coefficient estimation and model prediction based on the LASSO sparse learning algorithm and its improved versions such as Bolasso, bootstrap ranking LASSO, two-stage hybrid LASSO and others. These LASSO estimation procedures are applied in the fields of variable selection, graphical modeling and ensemble learning. The bagging LASSO model uses a Monte Carlo cross-entropy algorithm to determine the best base-level models and improve predictive performance.
|Author||Pi Guo, Yuantao Hao|
|Date of publication||2015-11-17 14:40:37|
|Maintainer||Pi Guo <firstname.lastname@example.org>|
Bagging.lasso: A Bagging Prediction Model Using LASSO Selection Algorithm.
Bolasso: Bolasso model.
BRLasso: Bootstrap ranking LASSO model.
Plot.importance: Generate a plot of variable importance.
Predict.bagging: Make predictions for new data from a 'bagging' object.
Print.bagging: Print a bagging object.
Sparse.graph: Graphic Modeling Using LASSO-Type Sparse Learning Algorithm.
TSLasso: Two-stage hybrid LASSO model.
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