Iterative Aggregation Method for Solving Principal Component Analysis Problems
Numerical Analysis
2016-03-01 v1 Information Retrieval
Machine Learning
Abstract
Motivated by the previously developed multilevel aggregation method for solving structural analysis problems a novel two-level aggregation approach for efficient iterative solution of Principal Component Analysis (PCA) problems is proposed. The course aggregation model of the original covariance matrix is used in the iterative solution of the eigenvalue problem by a power iterations method. The method is tested on several data sets consisting of large number of text documents.
Keywords
Cite
@article{arxiv.1602.08800,
title = {Iterative Aggregation Method for Solving Principal Component Analysis Problems},
author = {Vitaly Bulgakov},
journal= {arXiv preprint arXiv:1602.08800},
year = {2016}
}