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This project explores various data modeling methods in R for predictive analytics. We analyze data, compare models, tune parameters, evaluate performance metrics, and select the best model based on independent test results. The study provides in-depth insights into model comparisons and performance evaluation with supporting tables and figures. The final selected model is described, and its predictive capabilities are assessed on independent test data.
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Introduction • Background • Goal of the project
Methods section • Description of the data • Models and model comparison • Methods • Model tuning • Performance metrics • Model comparison • Software • R packages
Results section • Descriptives and univariate results (?) • Model comparisons • What did you see • Supporting tables/figures • Selected model • Describe the final selected model • Model performance on independent test data set
Discussion/Conclusion • Model comparison • Be sure not to over-state your conclusions • Anything unexpected? • Final model • Is it a good predictive model?
Supplementary material • R-Code • Any other supporting information you deem interesting • Note, this is not part of the 5 page limit