Exam 3 Flashcards
1
Q
What is supervised learning (Classification)?
A
The training data (observations, measurements, etc.) are accompanied by labels indicating the class of observations
2
Q
What is Unsupervised learning (clustering)?
A
3
Q
What do decision trees do?
A
identify ways to split a data set
4
Q
What does a decision tree start with?
A
Root Node
5
Q
What predicts discrete labels?
A
classification
6
Q
What predicts continuous quantity or values?
A
regression
7
Q
What does multi-class classification require?
A
requires that a sample only have one class
8
Q
What is a small portion of a decision tree called?
A
sub-tree
9
Q
Type of classification algorithms in machine learning? (4)
A
- linear classifiers
- k-nearest-neighbors - decision trees
- support vector machines
- neural networks
10
Q
Clustering vs Classification
A
11
Q
A
