dcase_util.datasets.Dataset.validation_split

Dataset.validation_split(fold=None, training_meta=None, split_type='balanced', validation_amount=None, seed=0, verbose=False, scene_label=None, iterations=100, **kwargs)[source]

List of validation files. Validation files are always subset of training files.

Parameters
foldint

Fold id, if None all meta data is returned. Default value None

training_metaMetaDataContainer

Training data meta container. Use this instead of fold parameter, if additional processing is needed for training meta before usage. Default value None

split_typestr

Split type [dataset, random, balanced] Default value ‘balanced’

validation_amountfloat

Amount of training files to be assigned for validation Default value None

seedint

Randomization seed Default value 0

verbosebool

Show information about the validation set. Default value False

scene_labelstr

Scene label of the validation set. If None, all training material used. Default value None

iterationsint

Randomization iterations done when finding balanced set before selecting best matched set. Default value 100

Returns
list of str

List containing all files assigned to training set for given fold.

list of str

List containing all files assigned to validation set for given fold.