Machine Learning
Principal Component Analysis
PCA
Machine Learning· Advanced
Definition
A dimensionality reduction technique that transforms high-dimensional data into a lower-dimensional representation by finding the directions (principal components) of maximum variance. Preserves the most informative structure in data while discarding noise.
Enterprise Context
Used for data visualization, feature reduction before model training, and detecting structure in high-dimensional datasets like genomics, financial time series, and sensor data.
Tags
#dimensionality-reduction#unsupervised#statistics
MS
Maxx Stacks Editorial
Reviewed by enterprise AI practitioners
Maxx University
Keep learning. Keep building.
250+ terms. 5 learning paths. AI maturity assessment. Jargon translator. All free, always.