• 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.
