Addressing Class Imbalance in Non-Profit Donor Response Prediction Using Random Forest Quantile Classifiers: A Comparative Analysis

Additional Metadata
Keywords	Non-profit organisations; Donor response prediction; Class Imbalance; Machine Learning; Random Forest Quantile (RFQ) Classifiers
Thesis Advisor	Gruber, K
Persistent URL	hdl.handle.net/2105/73751
Series	Econometrie
Organisation	Erasmus School of Economics
Citation APA Style AAA Style APA 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	Rupchandani, K.K.K. (2024, September 18). Addressing Class Imbalance in Non-Profit Donor Response Prediction Using Random Forest Quantile Classifiers: A Comparative Analysis. Econometrie. Retrieved from http://hdl.handle.net/2105/73751

Publication