1. Introduction to Classification & Clustering
Villanova University Machine Learning Project

2. Introduction to Classification & Clustering
Machine Learning
Getting a computer to learn from data
A type of Artificial Intelligence, where a computer does something "intelligent"
Ability of a computer to improve what it does in a way that mimics how humans learn, like with repetition or experience
Villanova University Machine Learning Project
Introduction to Classification & Clustering

3. Examples of Machine Learning
Face detection used by Facebook to help you automatically tag friends
Spam filters that get better over time at identifying and trashing spam s
Fraud detection that notices suspicious patterns of credit card use and you get a call
Optical character recognition that reads the numbers written on a check you deposit
Villanova University Machine Learning Project
Introduction to Classification & Clustering

4. Classification & Clustering
Two ways to put things into categories
Classification
Categories already exist
Put each thing into the category where it fits best
Clustering
Categories don’t yet exist
Put the things into brand new categories based on similar characteristics or features of the things
Villanova University Machine Learning Project
Introduction to Classification & Clustering

5. Introduction to Classification & Clustering
Some of the things being put into groups are already labeled with their "class." These class labels are used to guide or supervise the classification of unlabeled things into one of the classes.
When the classes are known ahead of time this type of machine learning is called:
Supervised Learning
Villanova University Machine Learning Project
Introduction to Classification & Clustering

6. Example: Classification
Dogs
Cats
Classify the photos on the next slide into one of these two categories
Villanova University Machine Learning Project
Introduction to Classification & Clustering

7. Example: Classification
Villanova University Machine Learning Project
Introduction to Classification & Clustering

8. How Did Classification Work?
How did you approach the task?
What made it easy to do?
What made it hard to do?
How good are your final categories?
Villanova University Machine Learning Project
Introduction to Classification & Clustering

9. Unsupervised Learning Introduction to Classification & Clustering
None of the things being put into groups already have their class labels so the grouping is unsupervised. The task becomes figuring out clusters of things with similar features.
When the classes are unknown ahead of time this type of machine learning is called:
Unsupervised Learning
Villanova University Machine Learning Project
Introduction to Classification & Clustering

10. Introduction to Classification & Clustering
Example: Clustering
Group 1
Group 2
Cluster the photos on the next slide into two categories. You decide!
Villanova University Machine Learning Project
Introduction to Classification & Clustering

11. Introduction to Classification & Clustering
Example: Clustering
Villanova University Machine Learning Project
Introduction to Classification & Clustering

12. How Did Clustering Work?
How did you approach the task?
What made it easy to do?
What made it hard to do?
How does it compare with Classification?
How good are your final categories?
Villanova University Machine Learning Project
Introduction to Classification & Clustering

13. Example: Clustering Again!
Group 1
Group 2
Group 3
Cluster the photos on the next slide into three categories. You decide!
Villanova University Machine Learning Project
Introduction to Classification & Clustering

14. Introduction to Classification & Clustering
Example: Clustering
Villanova University Machine Learning Project
Introduction to Classification & Clustering

15. How Did Clustering Work?
How did you create categories?
Did it get harder to do with more categories?
How good are your results?
Villanova University Machine Learning Project
Introduction to Classification & Clustering