Results for "regression"

Finding mathematical equations from data.

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

Average of squared residuals; common regression objective.

A subfield of AI where models learn patterns from data to make predictions or decisions, improving with experience rather than explicit rule-coding.

A parameterized mapping from inputs to outputs; includes architecture + learned parameters.

A scalar measure optimized during training, typically expected loss over data, sometimes with regularization terms.

The degree to which predicted probabilities match true frequencies (e.g., 0.8 means ~80% correct).

Automated detection/prevention of disallowed outputs (toxicity, self-harm, illegal instruction, etc.).

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

Measures divergence between true and predicted probability distributions.

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

Predicting future values from past observations.

Systematic error introduced by simplifying assumptions in a learning algorithm.

Persistent directional movement over time.

Estimating parameters by maximizing likelihood of observed data.

Expected causal effect of a treatment.

Running predictions on large datasets periodically.

Low-latency prediction per request.

Mathematical foundation for ML involving vector spaces, matrices, and linear transformations.

Number of linearly independent rows or columns.

Measure of spread around the mean.

Measures joint variability between variables.

Probabilities do not reflect true correctness.

Ability to correctly detect disease.

Requirement to provide explanations.

AI that ranks patients by urgency.

Grouping patients by predicted outcomes.

AI predicting crime patterns (highly controversial).

Models estimating recidivism risk.

Predicting case success probabilities.