1. Create a 2D classification problem that you can visualize, where only a few outliers cause a
Linear SVM to learn the wrong solution.
Linear SVM loss=∥w∥2+C⋅∑i=1nmax(1−wTx(i)⋅y(i))
2. Plot the boundy as learned by the scikit learn SVM class
3. Try to implement your own "Robust" Linear SVM loss function.
4. Show results of your Robust Linear SVM on the noisy traing data
DescriptionIn this final assignment, the students will demonstrate their ability to apply two ma
Path finding involves finding a path from A to B. Typically we want the path to have certain properties,such as being the shortest or to avoid going t
Develop a program to emulate a purchase transaction at a retail store. Thisprogram will have two classes, a LineItem class and a Transaction class. Th
1 Project 1 Introduction - the SeaPort Project series For this set of projects for the course, we wish to simulate some of the aspects of a number of
1 Project 2 Introduction - the SeaPort Project series For this set of projects for the course, we wish to simulate some of the aspects of a number of