Random Forest combined with scaled PCA: A proper enhancement of a computationally expensive ML method

Additional Metadata
Keywords	Random forest; PCA; sPCA; forecasting; stock returns; stock volatility; big data; dimension reduction; machine learning
Thesis Advisor	Opschoor, PA
Persistent URL	hdl.handle.net/2105/67559
Series	Econometrie
Organisation	Erasmus School of Economics
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	Geenen, K.R. (2023). Random Forest combined with scaled PCA: A proper enhancement of a computationally expensive ML method. In Econometrie.http://hdl.handle.net/2105/67559

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