CS4375 Project2 Solved

Description

For each data set, your project will be evaluated as follows:

•  You will get more points for larger/messier data sets:
  • 0-5 pts <30K o 6-10 pts >=30K
•  Data cleaning:
  • provide a link where you found the data
  • describe what steps you had to do for data cleaning (more points for messier data that needed cleaning)
•  Data exploration:
  • use at least 5 R functions for data exploration o create at least 2 informative R graphs for data exploration
•  Run at least 3 ML algorithms on each data set, using at least 5 algorithms in all.
  • this portion of your R script should include:
    • code to run the algorithms
    • commentary on feature selection you performed and why
    • code to compute your metrics for evaluation as well as commentary discussing the results
  •  Run at least one ensemble method such as Random Forest, XGBoost o this portion of your R script should include:
    • code to run the algorithms
    • commentary on feature selection you performed and why
    • code to compute your metrics for evaluation as well as commentary discussing the results
  •  Results analysis o rank the algorithms from best to worst performing on your data o add commentary on the performance of the algorithms
    • your analysis concerning why the best performing algorithm worked best on that data
    • commentary on what your script was able to learn from the data (big picture) and if this is likely to be useful

Project depth o 0-3 project minimally meets requirements o 4-6 project exceeds minimum requirements o 7-10 project went well above the requirements