AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |
Back to Blog
Pca return column3/5/2024 ![]() The PCA loadings data frame contains the loadings for each principal component, and the PCA explained variance data frame contains the percentage of explained variance for each principal component. The PCA scores data frame contains the category-column (class) and the scores for each principal component. The percentage of explained variance for each principal component is extracted, and the results are written to the output files. The script reads the data from the input file, extracts the first column as the category column (class), and then performs the PCA analysis on the remaining columns. The number of principal components to use is set to 4. The input file is an Excel file specified in the “path” variable, and the output files for PCA scores, loadings, and explained variance are specified in “output_path_scores,” “output_path_loadings,” and “output_path_var,” respectively. This R script performs a Principal Component Analysis (PCA) using the Non-linear Iterative Partial Least Squares (NIPALS) algorithm. ![]()
0 Comments
Read More
Leave a Reply. |