Statistics, Covariance Matrix, Eigenvectors, Pca Analysis, Machine Learning.
components of a dataset. Principal Component Analysis (PCA) PCA is a widely used technique for dimensionality reduction and feature extraction. It works by finding the eigenvectors and eigenvalues of the covariance matrix of the dataset. These eigenvectors, called principal components, represent