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Learners

Each of reward_model, contextual_policy, and best_arm accepts either a character string naming a built-in learner or a user-supplied object implementing the required fit / predict methods.

Built-in strings

slot strings backend
reward_model random_forest, linear, ridge, lasso scikit-learn
contextual_policy policy_tree, policy_forest, linear (aliases dr_econml_2, dr_econml) econml
best_arm ips, simple (aliases best_arm_erm, simple_best_arm) kpe

User-supplied-object protocols

kpe.learners.base.RewardModel

Bases: Protocol

kpe.learners.base.Policy

Bases: Protocol

kpe.learners.base.BestArm

Bases: Protocol

Resolver functions

kpe.learners.registry.resolve_reward(spec, *, seed=None)

kpe.learners.registry.resolve_policy(spec, *, seed=None)

kpe.learners.registry.resolve_best_arm(spec, *, seed=None)