Expected improvement

As explained in AI-Powered Search

Expected improvement is a Bayesian-optimization acquisition function that scores candidates by their expected gain over the current best result while accounting for predictive uncertainty.

How AI-Powered Search covers it

How deep it goes

Explains the basic formula and implementation, but defers advanced Bayesian-optimization details.

Examples

Uses product features, logged judgments, uncertainty tables, and a "transformers dvd" exploration query.

What it assumes

Assumes logged judgments and search features; supplies the Gaussian-process predictions and improvement calculation.

What you can do after

Apply it via Python to rank candidate feature vectors and select products for search-engine exploration.

How it connects

Connects Gaussian processes, Bayesian optimization, active learning, predictive uncertainty, and search ranking.

liveBookmanning.com

Read AI-Powered Search on liveBook Get the book at manning.com

Also explained in

• 

  liveBookmanning.com
  Bayesian Optimization in ActionExpected improvement is a Bayesian optimization acquisition function that quantifies the expected amount by which evaluating a candidate may improve on the best observed objective value.

Compare how 2 books explain expected improvement →

Related concepts

• Bayesian optimizationkind of · Bayesian optimization is a sequential method for optimizing an expensive or unknown objective by using a probabilistic model to guide evaluations.
• constrained expected improvementincludes · Constrained expected improvement is a Bayesian optimization acquisition function whose score is the expected improvement multiplied by the probability that the candidate satisfies the constraints.
• ExpectedHypervolumeImprovementincludes · ExpectedHypervolumeImprovement is a BoTorch acquisition-function class that computes analytic expected hypervolume improvement for multiobjective Bayesian optimization.
• policykind of · A policy is a rule, strategy, or mapping that governs or determines decisions, actions, permissions, or behavior under specified conditions.
• acquisition functionkind of · An acquisition function is a scoring rule that ranks candidate evaluations by their expected usefulness for selecting the next sample or experiment.

This explainer was generated by Manning's knowledge graph from the text of AI-Powered Search. The section links point to the parts of the book it draws on.