- Compete the two programming exercises described in the following charts.
- Start looking for an interesting dataset for your project.
Programming Exercise A
- Apply the Scikit Learn SVM Classifier to the Iris dataset using all three categories and all four feature at once and upload your .ipynb file.
- Run the SVM model (at least) four times using a different kernel each time. Compare and discuss the results for each of the kernels.
- Name your file lastname_firstname_AS04A.ipynb.
Programming Exercise B
- Apply the Scikit Learn Decision Tree Classifier to the Iris dataset using all three categories and all four feature at once and upload your .ipynb file.
- See if your choice of impurity measure makes a difference in your results.
- Name your file lastname_firstname_AS04B.ipynb.
Programming Exercises (both A and B)
- Discuss your findings.
- Include all of your discussion in your .ipynb file and submit the file through Blackboard.
- Do not clear your results after you last run so that I will be able to see your results without rerunning your code.
If you collaborate with anyone on this assignment, be sure to follow the collaboration guidelines in the syllabus
