miml.data.miml_dataset.MIMLDataset

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