I found the project’s goal to be very practical since it has the potential to save people’s life. I wonder if there was anything in common between the patients with missing values that were deleted from this experiment (i.e maybe they came from the same hospital). I like that your report was very detailed. For example, you included a table with every feature and a reason for it including or not including it from the project; I agree with all of your reasoning. I liked that you used one-hot encoding in your feature transformation step. I also liked your approach to select a representative sample (i.e selecting a county with a large number of observations and limiting the values of CCS Procedure Code). I liked how you created you tweaked the test error equation to better measure the quality of your model. I liked that you used your extended knowledge in statistics to apply methods outside the scope of the class, like random forest and neural network, and that you provided a description of each of these methods. I think that your report was very well organized. Your representation of your results was very concise and easy to read. I found the analysis of your results to be very helpful. I also liked that you acknowledged you resources. Great job!
I found the project’s goal to be very practical since it has the potential to save people’s life. I wonder if there was anything in common between the patients with missing values that were deleted from this experiment (i.e maybe they came from the same hospital). I like that your report was very detailed. For example, you included a table with every feature and a reason for it including or not including it from the project; I agree with all of your reasoning. I liked that you used one-hot encoding in your feature transformation step. I also liked your approach to select a representative sample (i.e selecting a county with a large number of observations and limiting the values of CCS Procedure Code). I liked how you created you tweaked the test error equation to better measure the quality of your model. I liked that you used your extended knowledge in statistics to apply methods outside the scope of the class, like random forest and neural network, and that you provided a description of each of these methods. I think that your report was very well organized. Your representation of your results was very concise and easy to read. I found the analysis of your results to be very helpful. I also liked that you acknowledged you resources. Great job!