Index

A

add_arm() (mab2rec.BanditRecommender method) alpha (mab2rec.LearningPolicy.LinTS attribute), [1] (mab2rec.LearningPolicy.LinUCB attribute), [1] (mab2rec.LearningPolicy.UCB1 attribute), [1]

B

backend (mab2rec.BanditRecommender attribute) BanditRecommender (class in mab2rec)

benchmark() (in module mab2rec.pipeline) binarizer (mab2rec.LearningPolicy.ThompsonSampling attribute), [1]

E

epsilon (mab2rec.LearningPolicy.EpsilonGreedy attribute), [1] (mab2rec.LearningPolicy.LinGreedy attribute), [1]

F

fit() (mab2rec.BanditRecommender method)

I

is_minibatch (mab2rec.NeighborhoodPolicy.Clusters attribute), [1]

K

k (mab2rec.NeighborhoodPolicy.KNearest attribute), [1]

L

l2_lambda (mab2rec.LearningPolicy.LinGreedy attribute), [1] (mab2rec.LearningPolicy.LinTS attribute), [1] (mab2rec.LearningPolicy.LinUCB attribute), [1] learning_policy (mab2rec.BanditRecommender attribute) LearningPolicy (class in mab2rec) LearningPolicy.EpsilonGreedy (class in mab2rec) LearningPolicy.LinGreedy (class in mab2rec)

LearningPolicy.LinTS (class in mab2rec) LearningPolicy.LinUCB (class in mab2rec) LearningPolicy.Popularity (class in mab2rec) LearningPolicy.Random (class in mab2rec) LearningPolicy.Softmax (class in mab2rec) LearningPolicy.ThompsonSampling (class in mab2rec) LearningPolicy.UCB1 (class in mab2rec)

M

mab (mab2rec.BanditRecommender attribute) mab2rec module mab2rec.pipeline module mab2rec.visualization module

metric (mab2rec.NeighborhoodPolicy.KNearest attribute), [1] (mab2rec.NeighborhoodPolicy.Radius attribute), [1] module mab2rec mab2rec.pipeline mab2rec.visualization

N

n_clusters (mab2rec.NeighborhoodPolicy.Clusters attribute), [1] n_dimensions (mab2rec.NeighborhoodPolicy.LSHNearest attribute), [1] n_jobs (mab2rec.BanditRecommender attribute) n_tables (mab2rec.NeighborhoodPolicy.LSHNearest attribute), [1] neighborhood_policy (mab2rec.BanditRecommender attribute) NeighborhoodPolicy (class in mab2rec)

NeighborhoodPolicy.Clusters (class in mab2rec) NeighborhoodPolicy.KNearest (class in mab2rec) NeighborhoodPolicy.LSHNearest (class in mab2rec) NeighborhoodPolicy.Radius (class in mab2rec) NeighborhoodPolicy.TreeBandit (class in mab2rec) no_nhood_prob_of_arm (mab2rec.NeighborhoodPolicy.LSHNearest attribute), [1] (mab2rec.NeighborhoodPolicy.Radius attribute), [1]

P

partial_fit() (mab2rec.BanditRecommender method) plot_inter_diversity_at_k() (in module mab2rec.visualization) plot_intra_diversity_at_k() (in module mab2rec.visualization) plot_metrics_at_k() (in module mab2rec.visualization) plot_num_items_per_recommendation() (in module mab2rec.visualization)

plot_personalization_heatmap() (in module mab2rec.visualization) plot_recommended_counts() (in module mab2rec.visualization) plot_recommended_counts_by_item() (in module mab2rec.visualization) predict() (mab2rec.BanditRecommender method) predict_expectations() (mab2rec.BanditRecommender method)

R

radius (mab2rec.NeighborhoodPolicy.Radius attribute), [1]

recommend() (mab2rec.BanditRecommender method) remove_arm() (mab2rec.BanditRecommender method)

S

scale (mab2rec.LearningPolicy.LinGreedy attribute), [1] (mab2rec.LearningPolicy.LinTS attribute), [1] (mab2rec.LearningPolicy.LinUCB attribute), [1]

score() (in module mab2rec.pipeline) seed (mab2rec.BanditRecommender attribute) set_arms() (mab2rec.BanditRecommender method)

T

tau (mab2rec.LearningPolicy.Softmax attribute), [1] top_k (mab2rec.BanditRecommender attribute)

train() (in module mab2rec.pipeline) tree_parameters (mab2rec.NeighborhoodPolicy.TreeBandit attribute), [1]

W

warm_start() (mab2rec.BanditRecommender method)