Results for "input variable"

Variable enabling causal inference despite confounding.

Variable whose values depend on chance.

A hidden variable influences both cause and effect, biasing naive estimates of causal impact.

Reduction in uncertainty achieved by observing a variable; used in decision trees and active learning.

Measures how much information an observable random variable carries about unknown parameters.

Describes likelihoods of random variable outcomes.

Learning a function from input-output pairs (labeled data), optimizing performance on predicting outputs for unseen inputs.

A measurable property or attribute used as model input (raw or engineered), such as age, pixel intensity, or token ID.

Designing input features to expose useful structure (e.g., ratios, lags, aggregations), often crucial outside deep learning.

Studying internal mechanisms or input influence on outputs (e.g., saliency maps, SHAP, attention analysis).

Local surrogate explanation method approximating model behavior near a specific input.

Model that compresses input into latent space and reconstructs it.

Sensitivity of a function to input perturbations.