Can GPT Alleviate Training Data Scarcity? An Experimental Study on the Potential of LLM-Generated Synthetic Data for Classification Learning Enhancement

Additional Metadata
Keywords	Synthetic Data, Classification, Few-Shot Prompt, GPT, Decision Tree, Naïve Bayes, Generative AI
Thesis Advisor	Kucukyilmaz, Tayfun, Koppius, Otto
Persistent URL	hdl.handle.net/2105/75150
Series	Business Information Management
Organisation	Rotterdam School of Management
Citation APA APA Style APA-ALL Style AAA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	van Koppen, Wouter. (2024). Can GPT Alleviate Training Data Scarcity? An Experimental Study on the Potential of LLM-Generated Synthetic Data for Classification Learning Enhancement. In Business Information Management.http://hdl.handle.net/2105/75150

Publication