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gptkbp:instanceOf
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statistical technique
regression analysis method
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gptkbp:adds
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L2 penalty
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gptkbp:alsoKnownAs
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gptkb:Tikhonov_regularization
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gptkbp:appliesTo
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gptkb:generalized_linear_models
linear regression
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gptkbp:assumes
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linear relationship
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gptkbp:biasVarianceTradeoff
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increases bias, reduces variance
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gptkbp:category
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gptkb:machine_learning
statistics
linear models
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gptkbp:citation
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gptkb:Hoerl,_A._E.,_&_Kennard,_R._W._(1970)._Ridge_regression:_Biased_estimation_for_nonorthogonal_problems._Technometrics,_12(1),_55-67.
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gptkbp:doesNotPerform
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variable selection
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gptkbp:effectOfLargeLambda
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shrinks coefficients toward zero
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https://www.w3.org/2000/01/rdf-schema#label
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Ridge regression
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gptkbp:introduced
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gptkb:Andrey_Tikhonov
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gptkbp:introducedIn
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1970
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gptkbp:lambda
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regularization parameter
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gptkbp:notRecommendedFor
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highly sparse solutions
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gptkbp:penaltyTerm
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lambda times sum of squared coefficients
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gptkbp:popularizedBy
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gptkb:Arthur_E._Hoerl
gptkb:Robert_W._Kennard
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gptkbp:reduces
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sum of squared residuals plus penalty
variance of estimates
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gptkbp:regularizes
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least squares estimates
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gptkbp:relatedTo
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gptkb:ordinary_least_squares
gptkb:Lasso_regression
gptkb:Elastic_net
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gptkbp:software
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gptkb:SAS
gptkb:MATLAB
gptkb:scikit-learn
R
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gptkbp:solutionFormula
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(X^T X + λI)^{-1} X^T y
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gptkbp:solvedBy
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overfitting
closed-form
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gptkbp:usedFor
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statistical analysis
multicollinearity
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gptkbp:bfsParent
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gptkb:Lasso_regression
gptkb:LASSO
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gptkbp:bfsLayer
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6
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