The table shows factor loadings of the acoustic parameters on the principal components showing eigenvalues >1 (PC1–PC4) extracted from the PCA. Note: *heaviest factor loadings (r>0.70).
Principal component analysis is a versatile tool to reduce dimensionality which has wide applications in statistics and machine learning. It is particularly useful for modeling data in high-dimensiona
