Review of Modeling Results

In order to develop a binary classification model to meet the business requirements of our client, we have now tried several modeling techniques with varying degrees of success. In the end, we'd like to choose the model with the best performance to do further analyses on and present to our client. However, it is also good to communicate the other options we explored, demonstrating a thoroughly researched project.

Here, we review the different models we tried for the case study problem, the hyperparameters we needed to tune, and the results from cross-validation or the validation set in the case of XGBoost. We only include the work we did using all possible features, not the earlier exploratory models where we used only one or two features:

Summary of modeling activities with case study data

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