10-701/15-781 Machine Learning, Fall 2005
Homework 3
Out: 10/20/05
Due: beginning of the class 11/01/05
Instructions. Contact [email protected] for question
Problem 1. Regression and Cross-validation [40 points]
Part 1: Multiple regression [15

10-701/15-781 Machine Learning, Fall 2007: Homework 2
Due: Wednesday, October 17th, beginning of the class
Instructions There are 4 questions on this assignment. The last question involves coding. Do not attach
your code to the writeup. Instead, copy your

Instance-based
Learning
Machine Learning 10701/15781
Carlos Guestrin
Carnegie Mellon University
February 14th, 2005
Announcements
Reminder: Second homework due Monday 21st
Why not just use Linear Regression?
Using data to predict new data
Nearest neighbor

Nave Bayes and Logistic Regression
Recommended reading:
Mitchell, Chapter 6.9, 6.10, 6.11.1
Bishop, Chapter 3.1.3, 3.1.4
Ng and Jordan paper
Machine Learning 10-701
Tom M. Mitchell
Center for Automated Learning and Discovery
Carnegie Mellon University

Logistic Regression
Machine Learning 10701/15781 Carlos Guestrin Carnegie Mellon University September 24th, 2007
Carlos Guestrin 2005-2007
1
Generative v. Discriminative classifiers Intuition
Want to Learn: h:X a Y
X features Y target classes
Bayes op

Matrix MLE for Linear Regression
Joseph E. Gonzalez
Some people have had some trouble with the linear algebra form of the MLE for multiple regression. I tried to find a nice
online derivation but I could not find anything helpful. So I have decide to deri

10701/15781 Machine Learning, Fall 2007: Homework 3
Due: Monday, November 5, beginning of the class
Instructions
There are 4 questions on this assignment. Problem 3 involves coding. Do not attach your code to the
writeup. Instead, copy your implementation

10701/15781 Machine Learning, Fall 2007: Homework 5
Due: Wednesday, December 5, to Monica by 3pm
Instructions
There are 4 questions on this assignment. Problem 3 involves coding. Do not attach your code to the
writeup. Instead, copy your implementation to

10701/15781 Machine Learning, Fall 2007: Homework 4
Due: Monday, November 19, beginning of the class
Instructions
There are 5 questions on this assignment. Problem 5 involves coding. Do not attach your code to the
writeup. Instead, copy your implementatio

10-701/15-781 Machine Learning, Fall 2007: Homework 1
Due: Wednesday, October 3rd, beginning of the class
Instructions There are 4 questions on this assignment. The last question involves coding. Do not attach
your code to the writeup. Instead, copy your

Bayesian Networks
Inference
Machine Learning 10701/15781
Carlos Guestrin
Carnegie Mellon University
March 21st, 2005
Class project
Homework 4 out today Due April 4th (2 weeks)
Includes 10/100 points for your project proposal
this part is due March 28th

Bayesian Networks
Representation
Machine Learning 10701/15781
Carlos Guestrin
Carnegie Mellon University
March 16th, 2005
Handwriting recognition
Character recognition, e.g., kernel SVMs
rr r
r
c
rr
a c
c
z b
Webpage classification
Company home page
vs
P

10-701/15-781 Machine Learning: Assignment 1
The assignment is due September 27, 2005 at the beginning of class.
Write your name in the top right-hand corner of each page submitted. No paperclips, folders, etc.
If you have any questions, email question

10-701/15-781 Machine Learning, Fall 2005
Assignment 2 SOLUTIONS
Out: 9/27/05
Due: beginning of class 10/06/05
If you have questions, please contact Mike Stilman <[email protected]>.
Linear Regression
1. (Noise in Linear Regression)[25 pts] Linear regressi

Suppor t Vector Machines
SUE ANN HONG
10/18/2007
THE MOST FAMOUS SLIDE *EVER*
X
X
X
O
O
O
O
O
O
O
X
O
O
X
X
X
PRIMAL: THE INTUITIVE VERSION
min |w|2 +C !
s.t. (w.x + b)y " 1-!
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PRIMAL: THE INTUITIVE VERSION
min |w|2 +C !
s.t. (w.x + b)y " 1-!
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10-701 and 15-781
Machine Learning
http:/www.cs.cmu.edu/~guestrin/Class/10701/
Carlos Guestrin
Tom Mitchell
Syllabus
Covers a wide range of Machine Learning
techniques from basic to state-of-the-art
You will learn about the methods you heard
about:
Nav

Two SVM tutorials linked in class website
(please, read both):
High-level presentation with applications (Hearst 1998)
Detailed tutorial (Burges 1998)
Support Vector
Machines
Machine Learning 10701/15781
Carlos Guestrin
Carnegie Mellon University
February

Logistic Regression,
Generative and Discriminative Classifiers
Recommended reading:
Ng and Jordan paper On Discriminative vs. Generative classifiers: A
comparison of logistic regression and nave Bayes, A. Ng and M.
Jordan, NIPS 2002.
Machine Learning 10-

Machine Learning,
Function Approximation and Version Spaces
Recommended reading: Mitchell, Chapter 2
Machine Learning 10-701
Tom M. Mitchell
Center for Automated Learning and Discovery
Carnegie Mellon University
January 10, 2005
Machine Learning:
Study of

10-701/15-781 Machine Learning: Assignment 4
Released: Nov 29. Revised: Dec 6
The assignment is due December 8, 2005 at the beginning of class.
Write your name in the top right-hand corner of each page submitted. No paperclips, folders, etc.
If you hav