<owl:Class xmlns="https://folio.openlegalstandard.org/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:v1="http://www.loc.gov/mads/rdf/v1#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" xmlns:folio="https://folio.openlegalstandard.org/" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:skos="http://www.w3.org/2004/02/skos/core#" rdf:about="https://folio.openlegalstandard.org/R9L9Wx0aMach3Vcq9rgrt2w">
  <rdfs:subClassOf rdf:resource="https://folio.openlegalstandard.org/RBHMad8oNmYXkYHOHZLCgqv"/>
  <rdfs:label>Data Augmentation</rdfs:label>
  <skos:altLabel>Augmented Data Generation</skos:altLabel>
  <skos:altLabel>Data Enhancement</skos:altLabel>
  <skos:altLabel>Dataset Expansion</skos:altLabel>
  <skos:definition>Data Augmentation is a technique used to enhance the size and quality of a training dataset by applying various transformations and alterations to existing data. This process helps in creating diverse training examples, which improves the robustness and performance of machine learning models.</skos:definition>
</owl:Class>
