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- Regularized_least_squares abstract "Regularized least squares (RLS) is a family of methods for solving the least-squares problem while using regularization to further constrain the resulting solution.RLS is used for two main reasons. The first comes up when the number of variables in the linear system exceeds the number of observations. In such settings, the ordinary least-squares problem is ill-posed and is therefore impossible to fit because the associated optimization problem has infinitely many solutions. RLS allows the introduction of further constraints that uniquely determine the solution.The second reason that RLS is used occurs when the number of variables does not exceed the number of observations, but the learned model suffers from poor generalization. RLS can be used in such cases to improve the generalizability of the model by constraining it at training time. This constraint can either force the solution to be \"sparse\" in some way or to reflect other prior knowledge about the problem such as information about correlations between features. A Bayesian understanding of this can be reached by showing that RLS methods are often equivalent to priors on the solution to the least-squares problem.".
- Regularized_least_squares wikiPageExternalLink class06_RLSSVM.pdf.
- Regularized_least_squares wikiPageExternalLink rlsslides.pdf.
- Regularized_least_squares wikiPageExternalLink enet_talk.pdf.
- Regularized_least_squares wikiPageID "48803892".
- Regularized_least_squares wikiPageLength "22895".
- Regularized_least_squares wikiPageOutDegree "83".
- Regularized_least_squares wikiPageRevisionID "708048926".
- Regularized_least_squares wikiPageWikiLink Bayesian_inference.
- Regularized_least_squares wikiPageWikiLink Category:Estimation_theory.
- Regularized_least_squares wikiPageWikiLink Category:Inverse_problems.
- Regularized_least_squares wikiPageWikiLink Category:Linear_algebra.
- Regularized_least_squares wikiPageWikiLink Cholesky_decomposition.
- Regularized_least_squares wikiPageWikiLink Complete_metric_space.
- Regularized_least_squares wikiPageWikiLink Convex_optimization.
- Regularized_least_squares wikiPageWikiLink Covariance.
- Regularized_least_squares wikiPageWikiLink Covariance_matrix.
- Regularized_least_squares wikiPageWikiLink Elastic_net_regularization.
- Regularized_least_squares wikiPageWikiLink Epsilon-insensitive_loss.
- Regularized_least_squares wikiPageWikiLink Gaussian_function.
- Regularized_least_squares wikiPageWikiLink Gauss–Markov_theorem.
- Regularized_least_squares wikiPageWikiLink Generalization_error.
- Regularized_least_squares wikiPageWikiLink Hilbert_space.
- Regularized_least_squares wikiPageWikiLink Hinge_loss.
- Regularized_least_squares wikiPageWikiLink Kernel_method.
- Regularized_least_squares wikiPageWikiLink Laplace_distribution.
- Regularized_least_squares wikiPageWikiLink Lasso.
- Regularized_least_squares wikiPageWikiLink Lasso_(statistics).
- Regularized_least_squares wikiPageWikiLink Least-angle_regression.
- Regularized_least_squares wikiPageWikiLink Least_squares.
- Regularized_least_squares wikiPageWikiLink Likelihood_function.
- Regularized_least_squares wikiPageWikiLink Lp_space.
- Regularized_least_squares wikiPageWikiLink Machine_learning.
- Regularized_least_squares wikiPageWikiLink Mean_squared_error.
- Regularized_least_squares wikiPageWikiLink Mercers_theorem.
- Regularized_least_squares wikiPageWikiLink Norm_(mathematics).
- Regularized_least_squares wikiPageWikiLink Normal_distribution.
- Regularized_least_squares wikiPageWikiLink Ordinary_least_squares.
- Regularized_least_squares wikiPageWikiLink Orthonormal_basis.
- Regularized_least_squares wikiPageWikiLink Positive-definite_kernel.
- Regularized_least_squares wikiPageWikiLink Positive_definiteness.
- Regularized_least_squares wikiPageWikiLink Prior_probability.
- Regularized_least_squares wikiPageWikiLink Proximal_gradient_method.
- Regularized_least_squares wikiPageWikiLink Quadratic_programming.
- Regularized_least_squares wikiPageWikiLink Rank_(linear_algebra).
- Regularized_least_squares wikiPageWikiLink Regularization_(mathematics).
- Regularized_least_squares wikiPageWikiLink Regularized_least_squares.
- Regularized_least_squares wikiPageWikiLink Representer_theorem.
- Regularized_least_squares wikiPageWikiLink Residual_sum_of_squares.
- Regularized_least_squares wikiPageWikiLink Spike_and_slab.
- Regularized_least_squares wikiPageWikiLink Split-Bregman_method.
- Regularized_least_squares wikiPageWikiLink Stepwise_regression.
- Regularized_least_squares wikiPageWikiLink Support_vector_machine.
- Regularized_least_squares wikiPageWikiLink Symmetric_function.
- Regularized_least_squares wikiPageWikiLink Symmetry.
- Regularized_least_squares wikiPageWikiLink Taxicab_geometry.
- Regularized_least_squares wikiPageWikiLink Tikhonov_regularization.
- Regularized_least_squares wikiPageWikiLink Total_variation_denoising.
- Regularized_least_squares wikiPageWikiLink Well-posed_problem.
- Regularized_least_squares wikiPageWikiLinkText "Regularized Least Squares".
- Regularized_least_squares wikiPageWikiLinkText "list".
- Regularized_least_squares wikiPageWikiLinkText "regularized least squares".
- Regularized_least_squares wikiPageUsesTemplate Template:Main.
- Regularized_least_squares wikiPageUsesTemplate Template:Reflist.
- Regularized_least_squares wikiPageUsesTemplate Template:Regression_bar.
- Regularized_least_squares subject Category:Estimation_theory.
- Regularized_least_squares subject Category:Inverse_problems.
- Regularized_least_squares subject Category:Linear_algebra.
- Regularized_least_squares hypernym Family.
- Regularized_least_squares comment "Regularized least squares (RLS) is a family of methods for solving the least-squares problem while using regularization to further constrain the resulting solution.RLS is used for two main reasons. The first comes up when the number of variables in the linear system exceeds the number of observations. In such settings, the ordinary least-squares problem is ill-posed and is therefore impossible to fit because the associated optimization problem has infinitely many solutions.".
- Regularized_least_squares label "Regularized least squares".
- Regularized_least_squares wasDerivedFrom Regularized_least_squares?oldid=708048926.
- Regularized_least_squares isPrimaryTopicOf Regularized_least_squares.