eigenvectorkeskiköinti
Eigenvectorkeskiköinti is a term that can be loosely translated from Finnish as "eigenvector averaging" or "eigenvector centroiding." It refers to a technique used in linear algebra and data analysis, particularly within the context of principal component analysis (PCA) or related dimensionality reduction methods.
The core idea involves calculating the average of a set of eigenvectors. When performing PCA, eigenvectors
Commonly, this averaging is performed using a weighted mean, where the weights might be derived from the
The resulting average vector can be interpreted as a principal direction of the dataset that is robust