About this document
Manual PCA Computation Guide by Caleb Terrel Orellana is a document available to read on EtoBox.
The document explains how to manually compute Principal Component Analysis (PCA), a method used in data science for dimensionality reduction. It outlines the steps involved, including standardizing the dataset, calculating the covariance matrix, and determining eigenvalues and eigenvectors. The process ultimately simplifies data analysis by reducing the number of variables while retaining essential information.
- Author
- Caleb Terrel Orellana
- Language
- EN