We introduce a new method for robust principal component analysis (PCA). Classical PCA is based on the empirical covariance matrix of the data and hence is highly sensitive to outlying observations.

Both principal components analysis (PCA) and orthogonal regression deal with finding a p-dimensional linear manifold minimizing a scale of the orthogonal distances of the m-dimensional data points to ...

Principal Component Analysis (PCA) from Scratch Using the Classical Technique with C# Transforming a dataset into one with fewer columns is more complicated than it might seem, explains Dr. James ...

Researchers at Nanjing University of Science and Technology (NJUST) developed PCA-3DSIM, a mathematically grounded ...

Transforming a dataset into one with fewer columns is more complicated than it might seem, explains Dr. James McCaffrey of Microsoft Research in this full-code, step-by-step machine learning tutorial.