Solved-Assignments 04- Solution

Description

• 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.

The City College of New York

CSc 59929 – Introduction to Machine Learning 4 Spring 2020 – Erik K. Grimmelmann, Ph.D.