Data Science, Machine Learning, Pca, Big Data, Principal Component.
partial least squares. Dimensionality reduction: Reduces features dimensionality, losing only a small amount of information. Outlier detection (improving data quality): Projects a set of variables in fewer dimensions and highlights extraneous values. How is PCA formulated though? Given a matrix X,