{"entity":{"id":"pca","kind":"term","name":"Principal component analysis (PCA) as a feature compressor","aka":["principal component analysis","PCA","principal components","PCA-256","PCA reduction","separate-block PCA","block-wise PCA","dimensionality reduction"],"tldr":"PCA rotates the data onto the directions of greatest variance and keeps the top few, compressing twenty thousand genes into a few hundred numbers before a model sees them.","summary":"Principal component analysis is a linear dimensionality reduction technique used in exploratory analysis and preprocessing (Wikipedia). Reducing a full transcriptome to about 256 components before ridge or Cox regression is a strong, cheap baseline and the extraction recipe for frozen foundation-model embeddings; reducing each modality separately before concatenation stops a small block (a few hundred proteins) being swamped by a large one (all genes). The components must be fitted on the training fold only.","asOf":"2026-09-24","wikipedia":"https://en.wikipedia.org/wiki/Principal_component_analysis","links":[{"label":"Wikipedia","url":"https://en.wikipedia.org/wiki/Principal_component_analysis"}],"tags":["cansim-terms"],"related":["cancer-ai-vocabulary"],"cancers":[],"sections":[],"technologies":[],"targets":[],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":["ridge-regression","embedding","data-leakage","ood-detection"],"trials":[],"people":[],"bottlenecks":[],"keyPapers":[],"journals":[],"dependsOn":[],"notes":["Listed in the CanSim terms map 1.0.0 (docs/onco/terms.json, generated 2026-09-24), CC BY 4.0, attribution: CanSim project, an open, public-data-first cancer foundation-model programme; CanSim page path /terms/pca."],"provenance":{"editedBy":"OnCo CanSim terms wave (Wikipedia summaries, standards and project pages, GDC and FDA pages, Europe PMC)","editedOn":"2026-09-24","note":"CanSim terms map 1.0.0 (docs/onco/terms.json, generated 2026-09-24), CC BY 4.0, attribution: CanSim project, an open, public-data-first cancer foundation-model programme"},"category":"Methods and models"},"route":"/terms/pca/","neighbours":{"term":[{"id":"cancer-ai-vocabulary","kind":"term","name":"Cancer AI vocabulary (CanSim terms map)","route":"/terms/cancer-ai-vocabulary/"},{"id":"data-leakage","kind":"term","name":"Data leakage in model evaluation","route":"/terms/data-leakage/"},{"id":"embedding","kind":"term","name":"Embedding (learned representation)","route":"/terms/embedding/"},{"id":"multimodal-fusion","kind":"term","name":"Multimodal fusion (early, late, modality dropout)","route":"/terms/multimodal-fusion/"},{"id":"ood-detection","kind":"term","name":"Out-of-distribution detection (Mahalanobis guard)","route":"/terms/ood-detection/"},{"id":"ridge-regression","kind":"term","name":"Ridge regression and the multilayer perceptron","route":"/terms/ridge-regression/"},{"id":"spagcn","kind":"term","name":"Spatially aware clustering (SpaGCN, KNN smoothing)","route":"/terms/spagcn/"}]}}