elliot.dataset.dataloader package

Submodules

elliot.dataset.dataloader.knowledge_aware_chains module

Module description:

class elliot.dataset.dataloader.knowledge_aware_chains.KnowledgeChainsDataObject(config, data_tuple, side_information_data, *args, **kwargs)

Bases: object

Load train and test dataset

build_dict(dataframe, users)

build_sparse()

build_sparse_ratings()

dataframe_to_dict(data)

get_test()

get_validation()

class elliot.dataset.dataloader.knowledge_aware_chains.KnowledgeChainsLoader(config, *args, **kwargs)

Bases: object

Load train and test dataset

check_timestamp(d: pandas.DataFrame) → pandas.DataFrame

generate_dataobjects() → List[object]

generate_dataobjects_mock() → List[object]

load_attribute_file(attribute_file, separator='\t')

load_dataset_dataframe(file_ratings, separator='\t', attribute_file=None, feature_file=None, properties_file=None, column_names=['userId', 'itemId', 'rating', 'timestamp'], additive=True, threshold=10)

load_dataset_dict(file_ratings, separator='\t', attribute_file=None, feature_file=None, properties_file=None, additive=True, threshold=10)

load_feature_names(infile, separator='\t')

load_item_set(ratings_file, separator='\t', itemPosition=1)

load_properties(properties_file)

read_splitting(folder_path)

reduce_attribute_map_property_selection(map, items, feature_names, properties, additive, threshold=10)

reduce_dataset_by_item_list(ratings_file, items, separator='\t')

elliot.dataset.dataloader.visual_dataloader module

Module description:

class elliot.dataset.dataloader.visual_dataloader.VisualDataObject(config, data_tuple, side_information_data, *args, **kwargs)

Bases: object

Load train and test dataset

build_dict(dataframe, users)

build_sparse()

build_sparse_ratings()

dataframe_to_dict(data)

get_test()

get_validation()

read_images(images_folder, image_set, size_tuple)

read_images_multiprocessing(images_folder, image_set, size_tuple)

static read_single_image(images_folder, image_set, size_tuple, image_path)

class elliot.dataset.dataloader.visual_dataloader.VisualLoader(config, *args, **kwargs)

Bases: object

Load train and test dataset

check_timestamp(d: pandas.DataFrame) → pandas.DataFrame

generate_dataobjects() → List[object]

generate_dataobjects_mock() → List[object]

load_dataset_dataframe(file_ratings, separator='\t', visual_feature_set=None, column_names=['userId', 'itemId', 'rating', 'timestamp'])

read_splitting(folder_path)

reduce_dataset_by_item_list(ratings_file, items, separator='\t')

Module contents