lars.hpp File Reference
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Classes | |
| class | LARS |
| An implementation of LARS, a stage-wise homotopy-based algorithm for l1-regularized linear regression (LASSO) and l1+l2 regularized linear regression (Elastic Net). More... | |
Namespaces | |
| mlpack | |
Linear algebra utility functions, generally performed on matrices or vectors. | |
| mlpack::regression | |
Regression methods. | |
Detailed Description
Definition of the LARS class, which performs Least Angle Regression and the LASSO.
Only minor modifications of LARS are necessary to handle the constrained version of the problem:
![\[ \min_{\beta} 0.5 || X \beta - y ||_2^2 + 0.5 \lambda_2 || \beta ||_2^2 \]](form_153.png)
subject to 
Although this option currently is not implemented, it will be implemented very soon.
mlpack is free software; you may redistribute it and/or modify it under the terms of the 3-clause BSD license. You should have received a copy of the 3-clause BSD license along with mlpack. If not, see http://www.opensource.org/licenses/BSD-3-Clause for more information.
Definition in file lars.hpp.