CS4375 Project2 Solved

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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

  • Project2_CS4375-qge6gt.zip