Index

_

__call__() (replay.metrics.CategoricalDiversity method) (replay.metrics.Coverage method) (replay.metrics.HitRate method) (replay.metrics.MAP method) (replay.metrics.MRR method) (replay.metrics.NDCG method) (replay.metrics.Novelty method) (replay.metrics.OfflineMetrics method) (replay.metrics.Precision method) (replay.metrics.Recall method) (replay.metrics.RocAuc method) (replay.metrics.Unexpectedness method) __init__() (replay.data.nn.TorchSequentialDataset method) (replay.data.nn.TorchSequentialValidationDataset method) (replay.experimental.models.ADMMSLIM method) (replay.experimental.models.cql.CQL method) (replay.experimental.models.DDPG method) (replay.experimental.models.dt4rec.dt4rec.DT4Rec method) (replay.experimental.models.ImplicitWrap method) (replay.experimental.models.LightFMWrap method) (replay.experimental.models.MultVAE method) (replay.experimental.models.NeuroMF method) (replay.experimental.models.ScalaALSWrap method) (replay.experimental.scenarios.obp_wrapper.OBPOfflinePolicyLearner method) (replay.experimental.scenarios.TwoStagesScenario method) (replay.metrics.CategoricalDiversity method) (replay.metrics.Coverage method) (replay.metrics.Experiment method) (replay.metrics.HitRate method) (replay.metrics.MAP method) (replay.metrics.MRR method) (replay.metrics.NDCG method) (replay.metrics.Novelty method) (replay.metrics.OfflineMetrics method) (replay.metrics.Precision method) (replay.metrics.Recall method) (replay.metrics.RocAuc method) (replay.metrics.Unexpectedness method) (replay.models.ALSWrap method) (replay.models.AssociationRulesItemRec method) (replay.models.ClusterRec method) (replay.models.ItemKNN method) (replay.models.KLUCB method) (replay.models.nn.Bert4Rec method) (replay.models.nn.SasRec method) (replay.models.RandomRec method) (replay.models.SLIM method) (replay.models.ThompsonSampling method) (replay.models.UCB method) (replay.models.Word2VecRec method) (replay.scenarios.Fallback method) (replay.splitters.cold_user_random_splitter.ColdUserRandomSplitter method) (replay.splitters.last_n_splitter.LastNSplitter method) (replay.splitters.new_users_splitter.NewUsersSplitter method) (replay.splitters.random_splitter.RandomSplitter method) (replay.splitters.ratio_splitter.RatioSplitter method) (replay.splitters.time_splitter.TimeSplitter method) (replay.splitters.two_stage_splitter.TwoStageSplitter method)

_get_metric_value_by_user() (replay.metrics.base_metric.Metric static method)

A

add_absent_log_cols() (replay.experimental.preprocessing.data_preparator.DataPreparator static method) add_result() (replay.metrics.Experiment method) ADMMSLIM (class in replay.experimental.models)

all_features (replay.data.FeatureSchema property) (replay.data.nn.TensorSchema property) ALSWrap (class in replay.models) AssociationRulesItemRec (class in replay.models)

B

Bert4Rec (class in replay.models.nn)

C

cache() (replay.data.Dataset method) cardinality (replay.data.FeatureInfo property) (replay.data.nn.TensorFeatureInfo property) categorical_features (replay.data.FeatureSchema property) (replay.data.nn.TensorSchema property) CategoricalDiversity (class in replay.metrics) check_df() (replay.experimental.preprocessing.data_preparator.DataPreparator method) ClusterRec (class in replay.models)

ColdUserRandomSplitter (class in replay.splitters.cold_user_random_splitter) column (replay.data.FeatureInfo property) (replay.data.nn.TensorFeatureSource property) columns (replay.data.FeatureSchema property) compare() (replay.metrics.Experiment method) copy() (replay.data.FeatureSchema method) Coverage (class in replay.metrics) CQL (class in replay.experimental.models.cql) CSRConverter (class in replay.preprocessing.converter)

D

DataPreparator (class in replay.experimental.preprocessing.data_preparator) Dataset (class in replay.data) DatasetLabelEncoder (class in replay.data.dataset_utils)

DDPG (class in replay.experimental.models) drop() (replay.data.FeatureSchema method) DT4Rec (class in replay.experimental.models.dt4rec.dt4rec)

E

embedding_dim (replay.data.nn.TensorFeatureInfo property)

EntityDaysFilter (class in replay.preprocessing.filters) Experiment (class in replay.metrics)

F

Fallback (class in replay.scenarios) feature_hint (replay.data.FeatureInfo property) (replay.data.nn.TensorFeatureInfo property) feature_schema (replay.data.Dataset property) feature_source (replay.data.FeatureInfo property) (replay.data.nn.TensorFeatureInfo property) feature_sources (replay.data.nn.TensorFeatureInfo property) feature_type (replay.data.FeatureInfo property) (replay.data.nn.TensorFeatureInfo property) FeatureHint (class in replay.data) FeatureInfo (class in replay.data) features (replay.data.nn.TorchSequentialBatch attribute) (replay.data.nn.TorchSequentialValidationBatch attribute)

FeatureSchema (class in replay.data) FeatureSource (class in replay.data) FeatureType (class in replay.data) filter() (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method) filter_by_query_id() (replay.data.nn.PandasSequentialDataset method) fit() (replay.data.dataset_utils.DatasetLabelEncoder method) (replay.data.nn.SequenceTokenizer method) (replay.experimental.preprocessing.data_preparator.Indexer method) (replay.experimental.scenarios.TwoStagesScenario method) (replay.models.Recommender method) fit_predict() (replay.models.Recommender method) fit_transform() (replay.data.dataset_utils.DatasetLabelEncoder method) (replay.data.nn.SequenceTokenizer method)

G

get() (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method) get_all_query_ids() (replay.data.nn.PandasSequentialDataset method) get_encoder() (replay.data.dataset_utils.DatasetLabelEncoder method) get_features() (replay.models.Recommender method) get_item_recency() (in module replay.utils.time) get_max_sequence_length() (replay.data.nn.PandasSequentialDataset method) get_nearest_items() (replay.models.AssociationRulesItemRec method)

get_query_id() (replay.data.nn.PandasSequentialDataset method) get_schema() (in module replay.data) get_sequence() (replay.data.nn.PandasSequentialDataset method) get_sequence_by_query_id() (replay.data.nn.PandasSequentialDataset method) get_sequence_length() (replay.data.nn.PandasSequentialDataset method) get_spark_session() (in module replay.utils.session_handler) GlobalDaysFilter (class in replay.preprocessing.filters) ground_truth (replay.data.nn.TorchSequentialValidationBatch attribute)

H

HitRate (class in replay.metrics)

I

ImplicitWrap (class in replay.experimental.models) index (replay.data.nn.TensorFeatureSource property) Indexer (class in replay.experimental.preprocessing.data_preparator) interaction_features (replay.data.FeatureSchema property) InteractionEntriesFilter (class in replay.preprocessing.filters) interactions (replay.data.Dataset property) interactions_encoder (replay.data.dataset_utils.DatasetLabelEncoder property) (replay.data.nn.SequenceTokenizer property) interactions_rating_column (replay.data.FeatureSchema property) interactions_rating_features (replay.data.FeatureSchema property) interactions_timestamp_column (replay.data.FeatureSchema property) interactions_timestamp_features (replay.data.FeatureSchema property) inverse_transform() (replay.experimental.preprocessing.data_preparator.Indexer method) is_cat (replay.data.nn.TensorFeatureInfo property) is_categorical_encoded (replay.data.Dataset property) is_num (replay.data.nn.TensorFeatureInfo property) is_seq (replay.data.nn.TensorFeatureInfo property)

item() (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method) item_count (replay.data.Dataset property) item_distribution() (in module replay.utils.distributions) item_features (replay.data.Dataset property) (replay.data.FeatureSchema property) item_features_encoder (replay.data.dataset_utils.DatasetLabelEncoder property) (replay.data.nn.SequenceTokenizer property) item_id_column (replay.data.FeatureSchema property) item_id_encoder (replay.data.dataset_utils.DatasetLabelEncoder property) (replay.data.nn.SequenceTokenizer property) item_id_feature (replay.data.FeatureSchema property) item_id_feature_name (replay.data.nn.TensorSchema property) item_id_features (replay.data.nn.TensorSchema property) item_ids (replay.data.Dataset property) ItemKNN (class in replay.models) items() (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method)

K

keep_common_query_ids() (replay.data.nn.PandasSequentialDataset static method) keys() (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method)

KFolds() (in module replay.splitters.k_folds) KLUCB (class in replay.models)

L

LastNSplitter (class in replay.splitters.last_n_splitter) LightFMWrap (class in replay.experimental.models) load() (in module replay.utils.model_handler) (replay.data.Dataset class method) (replay.data.nn.PandasSequentialDataset class method) (replay.data.nn.SequenceTokenizer class method)

logger (replay.experimental.preprocessing.data_preparator.DataPreparator property) LowRatingFilter (class in replay.preprocessing.filters)

M

MAP (class in replay.metrics) Metric (class in replay.metrics.base_metric) MinCountFilter (class in replay.preprocessing.filters) module replay.data replay.data.nn replay.experimental.scenarios.obp_wrapper replay.metrics replay.models replay.preprocessing replay.preprocessing.filters replay.scenarios replay.splitters

MRR (class in replay.metrics) MultVAE (class in replay.experimental.models)

N

name (replay.data.nn.TensorFeatureInfo property) names (replay.data.nn.TensorSchema property) NDCG (class in replay.metrics) NeuroMF (class in replay.experimental.models)

NewUsersSplitter (class in replay.splitters.new_users_splitter) Novelty (class in replay.metrics) numerical_features (replay.data.FeatureSchema property) (replay.data.nn.TensorSchema property) NumInteractionsFilter (class in replay.preprocessing.filters)

O

OBPOfflinePolicyLearner (class in replay.experimental.scenarios.obp_wrapper) OfflineMetrics (class in replay.metrics) optimize() (in module replay.models.base_rec.BaseRecommender) (replay.experimental.scenarios.obp_wrapper.OBPOfflinePolicyLearner method) (replay.experimental.scenarios.TwoStagesScenario method) (replay.scenarios.Fallback method)

P

Padder (class in replay.experimental.preprocessing.padder) padding_mask (replay.data.nn.TorchSequentialBatch attribute) (replay.data.nn.TorchSequentialValidationBatch attribute) PandasSequentialDataset (class in replay.data.nn) persist() (replay.data.Dataset method) PopRec (class in replay.models)

Precision (class in replay.metrics) predict() (replay.experimental.scenarios.obp_wrapper.OBPOfflinePolicyLearner method) (replay.experimental.scenarios.TwoStagesScenario method) (replay.models.Recommender method) predict_pairs() (replay.models.Recommender method) predict_step() (replay.models.nn.Bert4Rec method) (replay.models.nn.SasRec method)

Q

QuantileItemsFilter (class in replay.preprocessing.filters) query_and_item_id_encoder (replay.data.dataset_utils.DatasetLabelEncoder property) (replay.data.nn.SequenceTokenizer property) query_count (replay.data.Dataset property) query_features (replay.data.Dataset property) (replay.data.FeatureSchema property) query_features_encoder (replay.data.dataset_utils.DatasetLabelEncoder property) (replay.data.nn.SequenceTokenizer property) query_id (replay.data.nn.TorchSequentialBatch attribute) (replay.data.nn.TorchSequentialValidationBatch attribute)

query_id_column (replay.data.FeatureSchema property) query_id_encoder (replay.data.dataset_utils.DatasetLabelEncoder property) (replay.data.nn.SequenceTokenizer property) query_id_feature (replay.data.FeatureSchema property) query_id_feature_name (replay.data.nn.TensorSchema property) query_id_features (replay.data.nn.TensorSchema property) query_ids (replay.data.Dataset property) QueryPopRec (class in replay.models)

R

RandomRec (class in replay.models) RandomSplitter (class in replay.splitters.random_splitter) rating_feature_name (replay.data.nn.TensorSchema property) rating_features (replay.data.nn.TensorSchema property) RatioSplitter (class in replay.splitters.ratio_splitter) read_as_spark_df() (replay.experimental.preprocessing.data_preparator.DataPreparator static method) Recall (class in replay.metrics) Recommender (class in replay.models) replay.data module replay.data.nn module replay.experimental.scenarios.obp_wrapper module

replay.metrics module replay.models module replay.preprocessing module replay.preprocessing.filters module replay.scenarios module replay.splitters module reset_cardinality() (replay.data.FeatureInfo method) RocAuc (class in replay.metrics)

S

SasRec (class in replay.models.nn) save() (in module replay.utils.model_handler) (replay.data.Dataset method) (replay.data.nn.SequenceTokenizer method) ScalaALSWrap (class in replay.experimental.models) schema (replay.data.nn.PandasSequentialDataset property) SequenceGenerator (class in replay.experimental.preprocessing.sequence_generator) SequenceTokenizer (class in replay.data.nn) sequential_features (replay.data.nn.TensorSchema property)

Sessionizer (class in replay.preprocessing.sessionizer) SLIM (class in replay.models) smoothe_time() (in module replay.utils.time) source (replay.data.nn.TensorFeatureSource property) split() (in module replay.splitters.base_splitter.Splitter) State (class in replay.utils.session_handler) subset() (replay.data.Dataset method) (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method) Surprisal (class in replay.metrics)

T

tensor_dim (replay.data.nn.TensorFeatureInfo property) tensor_schema (replay.data.nn.SequenceTokenizer property) TensorFeatureInfo (class in replay.data.nn) TensorFeatureSource (class in replay.data.nn) TensorSchema (class in replay.data.nn) ThompsonSampling (class in replay.models) TimePeriodFilter (class in replay.preprocessing.filters) TimeSplitter (class in replay.splitters.time_splitter) timestamp_feature_name (replay.data.nn.TensorSchema property) timestamp_features (replay.data.nn.TensorSchema property) to_pandas() (replay.data.Dataset method) to_polars() (replay.data.Dataset method) to_spark() (replay.data.Dataset method) TorchSequentialBatch (class in replay.data.nn)

TorchSequentialDataset (class in replay.data.nn) TorchSequentialValidationBatch (class in replay.data.nn) TorchSequentialValidationDataset (class in replay.data.nn) train (replay.data.nn.TorchSequentialValidationBatch attribute) transform() (replay.data.dataset_utils.DatasetLabelEncoder method) (replay.data.nn.SequenceTokenizer method) (replay.experimental.preprocessing.data_preparator.DataPreparator method) (replay.experimental.preprocessing.data_preparator.Indexer method) (replay.experimental.preprocessing.padder.Padder method) (replay.experimental.preprocessing.sequence_generator.SequenceGenerator method) (replay.preprocessing.converter.CSRConverter method) (replay.preprocessing.sessionizer.Sessionizer method) TwoStageSplitter (class in replay.splitters.two_stage_splitter) TwoStagesScenario (class in replay.experimental.scenarios)

U

UCB (class in replay.models)

Unexpectedness (class in replay.metrics) unpersist() (replay.data.Dataset method)

V

values() (replay.data.FeatureSchema method) (replay.data.nn.TensorSchema method)

W

Wilson (class in replay.models)

Word2VecRec (class in replay.models)