Man pages for cramR
Cram Method for Efficient Simultaneous Learning and Evaluation
| BatchContextualEpsilonGreedyPolicy | Batch Contextual Epsilon-Greedy Policy |
| BatchContextualLinTSPolicy | Batch Contextual Thompson Sampling Policy |
| BatchLinUCBDisjointPolicyEpsilon | Batch Disjoint LinUCB Policy with Epsilon-Greedy |
| ContextualLinearBandit | Contextual Linear Bandit Environment |
| cram_bandit | Cram Bandit: On-policy Statistical Evaluation in Contextual... |
| cram_bandit_est | Cram Bandit Policy Value Estimate |
| cram_bandit_sim | Cram Bandit Simulation |
| cram_bandit_var | Cram Bandit Variance of the Policy Value Estimate |
| cram_estimator | Cram Policy Estimator for Policy Value Difference (Delta) |
| cram_expected_loss | Cram ML Expected Loss Estimate |
| cram_learning | Cram Policy Learning |
| cram_ml | Cram ML: Simultaneous Machine Learning and Evaluation |
| cram_policy | Cram Policy: Efficient Simultaneous Policy Learning and... |
| cram_policy_value_estimator | Cram Policy: Estimator for Policy Value (Psi) |
| cram_simulation | Cram Policy Simulation |
| cram_var_expected_loss | Cram ML: Variance Estimate of the crammed expected loss... |
| cram_variance_estimator | Cram Policy: Variance Estimate of the crammed Policy Value... |
| cram_variance_estimator_policy_value | Cram Policy: Variance Estimate of the crammed Policy Value... |
| fit_model | Cram Policy: Fit Model |
| fit_model_ml | Cram ML: Fit Model ML |
| get_betas | Generate Reward Parameters for Simulated Linear Bandits |
| LinUCBDisjointPolicyEpsilon | LinUCB Disjoint Policy with Epsilon-Greedy Exploration |
| ml_learning | Cram ML: Generalized ML Learning |
| model_predict | Cram Policy: Predict with the Specified Model |
| model_predict_ml | Cram ML: Predict with the Specified Model |
| set_model | Cram Policy: Set Model |
| test_baseline_policy | Validate or Set the Baseline Policy |
| test_batch | Validate or Generate Batch Assignments |
| validate_params | Cram Policy: Validate User-Provided Parameters for a Model |
| validate_params_fnn | Cram Policy: Validate Parameters for Feedforward Neural... |
