Results for Exercise Sheet 11 (Margin size of Naive Bayes)
Please add your row to the table below, following the examples already there. The number of outliers is the number of points on the "wrong" side of the hyperplane implicitly computed by Naive Bayes (see Exercise 11.1). The margin size is the minium distance of the points from one class to the hyperplan + the minimum distance of the points from the other class to the hyperplane, ignoring all outliers. TODO: provide the SVM margin size from the lecture here. The one from Naive Bayes can not be larger.
Name |
Actor vs. Politician |
Singer vs. Songwriter |
||||
#outliers |
margin size |
precision |
#outliers |
margin size |
precision |
|
Björn |
5 |
0.09 |
98% |
76 |
0.08 |
83% |