matlab pca-loading

PCA loading in MATLAB refers to the weights assigned to each variable in the principal component analysis (PCA) model. These weights are also known as loadings or coefficients and represent the contribution of each variable to the principal component.

To calculate PCA loadings in MATLAB, you need to perform the PCA analysis using the built-in function "pca". The output of this function includes the principal component scores and loadings.

Here is an example code to calculate PCA loadings for a dataset:

% Load dataset
load fisheriris

% Perform PCA analysis
[coeff, score, latent] = pca(meas);

% Extract the loadings
loadings = coeff(:,1:2);

% Plot the loadings
figure
biplot(loadings,'Scores',score(:,1:2),'VarLabels',{'Sepal Length','Sepal Width','Petal Length','Petal Width'})

In this example, we load the iris dataset and perform PCA analysis using the "pca" function. We then extract the first two loadings (coefficients) using the "coeff" variable and plot them using the "biplot" function. The plot shows the contribution of each variable to the two principal components.