miml.data.miml_dataset.MIMLDataset

class miml.data.miml_dataset.MIMLDataset

Class to manage MIML data obtained from datasets

__init__() → None

Constructor of the class MIMLDataset

Methods

__init__()	Constructor of the class MIMLDataset
add_attribute(name[, position, values, feature])	Add attribute to the dataset
add_bag(bag)	Add a bag to the dataset
add_instance(bag, instance)	Add an Instance to a Bag of the dataset
cardinality()	Computes the Cardinality as the average number of labels per pattern.
delete_attribute(position)	Delete attribute of the dataset
delete_bag(key_bag)	Delete a bag of the dataset
delete_instance(bag, index_instance)	Delete an instance of a bag of the dataset
density()	Computes the density as the cardinality / numLabels.
describe()	Print statistics about the dataset
distinct()	Computes the numbers of labels combinations used in the dataset respect all the possible ones
get_attribute(bag, instance, attribute)	Get value of an attribute of the bag
get_attributes()	Get attributes values of the dataset
get_attributes_name()	Get attributes name
get_bag(bag)	Get data of a bag of the dataset
get_features()	Get features values of the dataset
get_features_by_bag()	Get features values of the dataset by bag
get_features_name()	Get function for dataset features name
get_instance(bag, index_instance)	Get an Instance of the dataset
get_labels()	Get labels values of the dataset
get_labels_by_bag()	Get labels values of the dataset
get_labels_name()	Get function for dataset labels name
get_name()	Get function for dataset name
get_number_attributes()	Get numbers of attributes of the bag
get_number_bags()	Get numbers of bags of the dataset
get_number_features()	Get numbers of attributes of the dataset
get_number_instances()	Get numbers of instances of the dataset
get_number_labels()	Get numbers of labels of the dataset
get_statistics()	Calculate statistics of the dataset
save_arff(path)
save_csv(path)
set_attribute(bag, index_instance, ...)	Update value from attributes
set_features_name(features)	Set function for dataset features name
set_labels_name(labels)	Set function for dataset labels name
set_name(name)	Set function for dataset name
show_dataset([start, end, attributes, mode, ...])	Function to show information about the dataset
split_dataset([train_percentage, seed])	Split dataset in two parts, one for training and the other for test
split_dataset_cv([folds, seed])	CrossValidation K-Fold split of dataset