Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method
Improving the Accuracy of Principal Component Analysis by the Maximum Entropy Method
Classical Principal Component Analysis (PCA) approximates data in terms of projections on a small number of orthogonal vectors. There are simple procedures to efficiently compute various functions of the data from the PCA approximation. The most important function is arguably the Euclidean distance between data items. This can be used, …