Tech Insights
PCA

PCA

Last updated , generated by Sumble
Explore more →

What is PCA?

Principal Component Analysis (PCA) is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. PCA is used for dimensionality reduction, feature extraction, and data visualization, especially when dealing with high-dimensional data.

What other technologies are related to PCA?

PCA Competitor Technologies

Canonical Correlation Analysis (CCA) is a related dimensionality reduction technique that aims to find correlations between two sets of variables.
mentioned alongside PCA in 25% (319) of relevant job posts
t-distributed Stochastic Neighbor Embedding (t-SNE) is another dimensionality reduction technique, often used for visualization.
mentioned alongside PCA in 53% (93) of relevant job posts
t-distributed Stochastic Neighbor Embedding (t-SNE) is another dimensionality reduction technique, often used for visualization.
mentioned alongside PCA in 64% (61) of relevant job posts
Uniform Manifold Approximation and Projection (UMAP) is a more modern dimensionality reduction technique that can be used as an alternative to PCA or t-SNE.
mentioned alongside PCA in 44% (72) of relevant job posts

PCA Complementary Technologies

Singular Value Decomposition (SVD) is the mathematical foundation for PCA. PCA is typically implemented using SVD.
mentioned alongside PCA in 55% (106) of relevant job posts
Support Vector Machines can benefit from PCA as a pre-processing step to reduce dimensionality and improve performance.
mentioned alongside PCA in 8% (351) of relevant job posts
DBSCAN is a clustering algorithm. PCA can be used as a pre-processing step to reduce the dimensionality of the data before applying DBSCAN.
mentioned alongside PCA in 22% (73) of relevant job posts

Which organizations are mentioning PCA?

Organization
Industry
Matching Teams
Matching People
PCA
Oracle
Scientific and Technical Services
PCA
McDonald's
Accommodation and Food Services

This tech insight summary was produced by Sumble. We provide rich account intelligence data.

On our web app, we make a lot of our data available for browsing at no cost.

We have two paid products, Sumble Signals and Sumble Enrich, that integrate with your internal sales systems.