ridge regression in matlab

To perform ridge regression in MATLAB, you can use the ridge function. The ridge function calculates the ridge regression coefficients for a given predictor matrix and response variable.

Here is an example of how to use the ridge function to perform ridge regression in MATLAB:

main.m
% Generate some sample data
X = randn(100, 5);   % predictor matrix with 100 observations and 5 variables
y = randn(100, 1);   % response variable

% Perform ridge regression
lambda = 0.1;        % regularization parameter
B = ridge(y, X, lambda);

% Display the ridge regression coefficients
disp(B);
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In this example, the ridge function takes three arguments: the response variable y, the predictor matrix X, and the regularization parameter lambda. The output B is a vector of the ridge regression coefficients.

Note that you can choose different values for the regularization parameter lambda to control the amount of regularization applied in the ridge regression.

Make sure you have the Statistics and Machine Learning Toolbox installed to use the ridge function in MATLAB.