Methods › Computer Vision › Image Denoising Models › PCA

Principal Components Analysis

PCA

1,323 papers tagged archive 2025-07-28

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

Principle Components Analysis (PCA) is an unsupervised method primary used for dimensionality reduction within machine learning. PCA is calculated via a singular value decomposition (SVD) of the design matrix, or alternatively, by calculating the covariance matrix of the data and performing eigenvalue decomposition on the covariance matrix. The results of PCA provide a low-dimensional picture of the structure of the data and the leading (uncorrelated) latent factors determining variation in the data.

Image Source: Wikipedia

Papers archive 2025-07-28

30 shown of 1,323, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 435 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Dimensionality Reduction304
Clustering92
General Classification70
Classification59
feature selection47
regression41
Time Series35
BIG-bench Machine Learning32
Time Series Analysis32
Anomaly Detection31
Denoising31
Face Recognition29
Retrieval29
Image Classification28
Matrix Completion27
Representation Learning26
image-classification26
Vocal Bursts Intensity Prediction23
Computational Efficiency22
Diagnostic18

Usage over time archive 2025-07-28

Papers per year tagged with PCA: 2006 to 2025, peak 166 166 0 2006: 1 paper 2006 2007: 1 paper 2008: 6 papers 2008 2009: 3 papers 2010: 11 papers 2010 2011: 4 papers 2012: 9 papers 2012 2013: 39 papers 2014: 48 papers 2014 2015: 52 papers 2016: 63 papers 2016 2017: 88 papers 2018: 95 papers 2018 2019: 113 papers 2020: 123 papers 2020 2021: 166 papers 2022: 126 papers 2022 2023: 136 papers 2024: 141 papers 2024 2025: 98 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (1,323 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Image Denoising ModelsDimensionality Reduction

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections