Homework 8#
Deadline
Due Sunday November 17 at midnight on Crowdmark.
This homework covers 3 classes:
Mon 11/11, we covered 9.1 - Maximal Margin Classifier
Weds 11/13, we covered 9.2 Support Vector Classifiers
Fri 11/15, we covered 9.3, 9.4 Support Vector Machines
Problems listed below are from the textbook.
9.7.3 Parts (a) through (f).
I’ve created a desmos toy to help you: https://www.desmos.com/calculator/hvfkvby64z
Feel free to include marked up screenshots of that tool in your explanation.
Please note that it does not provide a unit length vector, so be sure to modify your answer to part (b) accordingly.
9.7.8 Uses the
OJ.csv
data set included in the DataSets folder. Do all parts, but notes are below.(b) Use
C=1
(the default) instead of the book’sC = 0.01
information.(d) Use
GridSearchCV
like we used in class. You can useC = [0.01, 0.1, 1, 10]
in the range. However, we have noticed that particularly for the linear kernel,GridSearchCV
can be incredibly slow. If you are having issues getting the results to finish, feel free to use a subset ofC
values from above, or setcv=5
to use fewer splits in the \(k\)-fold CV.
Important
Standard instructions for submissions and deadlines can be found on the Homework Info Page.