How to set weights in fitcsvm?

Hello

I'm using the fitcsvm method from Matlab to train a SVM. The BoxConstraint parameter is the C (cost). Because I have high class imbalance (2 class classification problem), I would like to set different weights for each class.

How can this be done in fitcsvm?

In the LibSVM library there is an option to set different weights for each class...

Answer 1

[Abhipsa]

Hi @Tom Gerard,

To handle class imbalance in the “fitcsvm” function using the “Weights” parameter of the “BoxConstraint”, you can assign different weights to each observation based on its class.

This effectively gives more importance to the minority class during training.

The below code segment demonstrates how to achieve the same :

% Example data
X = [randn(100, 2); randn(20, 2) + 3]; % Features
Y = [ones(100, 1); -ones(20, 1)];      % Labels

% Calculate class weights
% Assuming class 1 is the majority class and class -1 is the minority
numClass1 = sum(Y == 1);
numClassMinus1 = sum(Y == -1);

% Assign weights inversely proportional to class frequency so as to give higher weightage to the minority class
weightClass1 = 1;
weightClassMinus1 = numClass1 / numClassMinus1;

% Create a weight vector for each observation
weights = ones(size(Y));
weights(Y == -1) = weightClassMinus1;

% Train the SVM with weights
SVMModel = fitcsvm(X, Y, 'Weights', weights);

% Display the model
disp(SVMModel);

For more details please refer to the following MathWorks documentation for "fitcsvm" for more details:

https://www.mathworks.com/help/releases/R2024b/stats/fitcsvm.html

Hope this helps!