W(1,2,3) Flashcards
1
Q
Supervised learning
A
2
Q
Hypothesis and hypothesis class
A
3
Q
Loss function
A
4
Q
Test Error, Training set error
A
5
Q
Linear classifiers, what are algorithms, what is form?
A
6
Q
Perceptron
A
7
Q
linear separability
margin of labeled data point/ margin of dataset
A
8
Q
Perceptron convergence Theorem
A
9
Q
Transforming data
A
10
Q
Polynomial basis transformation
A
11
Q
Feature mapping, name some methods
A
12
Q
Standardization of numerical features, how is it done?
A
