Assignment:
watch the 2 short lectures on Naive Bayes and Spam Filters and Word clouds. (You watched the first 10 seconds last week, so I know everyone can see it)
2. Refer back to the old slides on decision trees if you don’t remember them
3. Either find a data set you like or use this one https://www.kaggle.com/c/titanic/data and build a decision tree based on the data.
4. You may use either R or Python. If you want to get fancy, see com/2013/06/plotting-classification-and-regression-trees-with-plotrpart.html”>http://blog.revolutionanalytics.com/2013/06/plotting-classification-and-regression-trees-with-plotrpart.html
5. Using the same data set from above do a Naive Bayes classification on the data like in the video lecture above.
6. Compare the results between your Decision Tree and the Naive Bayes algorithm. Which is more accurate?
7. Paste summary and plots into a Microsoft Word document or Excel or Jupyter notebook and create a pdf or html file so I don’t have to compile your code to get an answer.
Data is attached below in .zip file
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