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
LinUCBDisjointPolicyEpsilon
                        LinUCB Disjoint Policy with Epsilon-Greedy
                        Exploration
cram_bandit             Cram Bandit: On-policy Statistical Evaluation
                        in Contextual Bandits
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 Evaluation
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 estimate
cram_variance_estimator
                        Cram Policy: Variance Estimate of the crammed
                        Policy Value Difference (Delta)
cram_variance_estimator_policy_value
                        Cram Policy: Variance Estimate of the crammed
                        Policy Value estimate (Psi)
fit_model               Cram Policy: Fit Model
fit_model_ml            Cram ML: Fit Model ML
get_betas               Generate Reward Parameters for Simulated Linear
                        Bandits
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 Networks (FNNs)
