Compete the two programming exercises described in the following charts.
Start looking for an interesting dataset for your project.
The City College of New York
CSc 59929 – Introduction to Machine Learning
Spring 2020 – Erik K. Grimmelmann, Ph.D.
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.
The City College of New York
CSc 59929 – Introduction to Machine Learning 2 Spring 2020 – Erik K. Grimmelmann, Ph.D.
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.
The City College of New York
CSc 59929 – Introduction to Machine Learning 3 Spring 2020 – Erik K. Grimmelmann, Ph.D.
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.
The City College of New York
CSc 59929 – Introduction to Machine Learning 4 Spring 2020 – Erik K. Grimmelmann, Ph.D.
