{"entity":{"id":"ridge-regression","kind":"term","name":"Ridge regression and the multilayer perceptron","aka":["ridge regression","L2 regularisation","L2-regularised regression","ridge head","multilayer perceptron","MLP","feedforward network","MLP head"],"tldr":"Ridge regression is linear regression with a penalty that shrinks coefficients, which keeps it stable when there are more genes than samples; a multilayer perceptron is the simplest neural network, a few fully connected layers.","summary":"Ridge regression estimates multiple-regression coefficients when the variables are highly correlated, by adding an L2 penalty (Wikipedia); with twenty thousand correlated genes and a few hundred samples it is the natural per-drug or per-outcome head on top of principal components. A multilayer perceptron is a feedforward network of fully connected layers with non-linear activations (Wikipedia), the usual encoder in autoencoders and the usual non-linear baseline; when it does not beat ridge, the non-linearity is not buying anything.","asOf":"2026-09-24","wikipedia":"https://en.wikipedia.org/wiki/Ridge_regression","links":[{"label":"Wikipedia: multilayer perceptron","url":"https://en.wikipedia.org/wiki/Multilayer_perceptron"},{"label":"Wikipedia","url":"https://en.wikipedia.org/wiki/Ridge_regression"}],"tags":["cansim-terms"],"related":["cancer-ai-vocabulary"],"cancers":[],"sections":[],"technologies":[],"targets":[],"drugs":[],"companies":[],"institutions":[],"pathways":[],"terms":["linear-probe","pca","logistic-regression-term","cross-entropy-mse"],"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/ridge-regression."],"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/ridge-regression/","neighbours":{"term":[{"id":"cancer-ai-vocabulary","kind":"term","name":"Cancer AI vocabulary (CanSim terms map)","route":"/terms/cancer-ai-vocabulary/"},{"id":"drug-response-baselines","kind":"term","name":"Drug-response baselines and frameworks: mean-drug floor, LightGBM, DrEval, IMPROVE, DeepTTA","route":"/terms/drug-response-baselines/"},{"id":"linear-probe","kind":"term","name":"Linear probe","route":"/terms/linear-probe/"},{"id":"logistic-regression-term","kind":"term","name":"Logistic regression and nearest-centroid classifiers","route":"/terms/logistic-regression-term/"},{"id":"cross-entropy-mse","kind":"term","name":"Loss functions: cross-entropy and mean squared error","route":"/terms/cross-entropy-mse/"},{"id":"pca","kind":"term","name":"Principal component analysis (PCA) as a feature compressor","route":"/terms/pca/"}]}}