Principal component analysis (PCA) is a mathematical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of uncorrelated variables called principal components. The number of principal components is less than or equal to the number of original variables.has passed the test.




File list:
PCA Example
..........\do_cca_prediction.m
..........\do_cca_training.m
..........\eof_analysis.m
..........\eof_project.m
..........\principal_component_analysis.m