Abstract
Chapters 12-14, used a variety of different philosophies and techniques to predict grant-funding success. In this chapter we compare and contrast the models' performance on a specific test set and demonstrate how to select the optimal final model.
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Notes
- 1.
As previously noted, more formal statistical methods are much better at making inferential statements on the importance of the predictors than variable importance measures.
References
Robin X, Turck N, Hainard A, Tiberti N, Lisacek F, Sanchez JC, Muller M (2011). “pROC: an open-source package for R and S+ to analyze and compare ROC curves.” BMC Bioinformatics, 12(1), 77.
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Kuhn, M., Johnson, K. (2013). A Summary of Grant Application Models. In: Applied Predictive Modeling. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6849-3_15
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DOI: https://doi.org/10.1007/978-1-4614-6849-3_15
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