CS464
Introduction to
Machine Learning
K-Nearest Neighbour
Bilkent University
Parametric Methods
Non-parametric Methods
Typically dont make distributional assumptions
Today we will see an example of
Islamic University of Gaza
Faculty of Engineering
Computer Engineering Department
Information Storage and Retrieval (ECOM 5124)
IR
_
HW 1
Boolean Retrieval
Eng. Mohammed Abdualal
February 14, 2015
Exe
CS464
Introduction to
Machine Learning
Lecture 11
znur Tatan
Bilkent University
Administrivia
Homework 2 is due Nov 19 Sunday 22:00 pm
Exam on Nov 26 Tuesday 6:00 pm
Everything covered in lectures
CS464
Introduction to
Machine Learning
Lecture 8
znur Tatan
Bilkent University
Administrivia
Next deadlines on the project:
Progress Presentation Nov 18, 20 2013 in class
Progress Report Nov 21 201
CS464
Introduction to
Machine Learning
Lecture 10
znur Tatan
Bilkent University
Administrivia
Next deadlines on the project:
Progress Presentation Dec 2, 20 2013 in class
Progress Report Dec 4 2013
CS464
Introduction to
Machine Learning
Lecture 7
znur Tatan
Bilkent University
Administrivia
Project Proposal Presentation, Oct 23 Wed, in
class, 5% of the project grade
Upload your ppt, pptx or pdf
CHAPTER 1
GENERATIVE AND DISCRIMINATIVE
CLASSIFIERS:
NAIVE BAYES AND LOGISTIC REGRESSION
Machine Learning
Copyright c 2005, 2010. Tom M. Mitchell. All rights reserved.
*DRAFT OF January 19, 2010*
*PLE
CS464
Introduction to
Machine Learning
Lecture 9
znur Tatan
Bilkent University
Administrivia
Next deadlines on the project:
- Progress Report Dec 2 2013, 5:00 pm
Progress Presentation Dec 4, 20 2013
CS464
Introduction to
Machine Learning
Lecture 6
znur Tatan
Bilkent University
Administrivia
Homework is due this Friday 5:00 pm sharp
(Moodle upload will be closed after that).
Detailed Project Inf
CS464
Introduction to
Machine Learning
Nave Bayes (1/3)
Bilkent University
Last Lecture: Density Estimation
2
Outline Today
Nave Bayes Classifier
3
A Bayesian Classifier
Classify the example into th
CS464
Introduction to
Machine Learning
Nave Bayes (2/3)
Bilkent University
Outline
Continue Nave Bayes Classifier
2
A Bayesian Classifier
This is our classifier the class label that is most probable
CS464
Introduction to
Machine Learning
Logistic Regression
Bilkent University
Logistic Regression
Name is somewhat misleading.
It is a technique for classification, not regression.
Linear regression
CS464
Introduction to
Machine Learning
Classification Performance Metrics
Bilkent University
Outline
Classification Metrics
Model Selection and Validation
Learning typically involves trying out diff
CS464
Introduction to
Machine Learning
Lecture 2
Bilkent University
Administrivia
Please check Moodle for the syllabus and required
readings
Outline
Probability and statistics review
Basic concep
In Class Exercises - Probability and Statistics Review
February 9, 2016
Question 1
In a college classroom of engineering majors, 41 percent of students own a smart phone, 35 percent of
students own a
CS464
Introduction to
Machine Learning
CS464
Bilkent University
Welcome to CS464!
Logistics
Instructors
znur Tatan
e-mail: oznur.tastan@cs.bilkent.edu.tr
Office: EA 429
Office hours: By appointme
CS464
Introduction to
Machine Learning
Estimation
Bilkent University
Outline
Density Estimation
MLE
MAP
Where do we get these probability estimates?
Density Estimation
How do we learn these proba
CS464
Introduction to
Machine Learning
Nave Bayes (3/3)
Bilkent University
Gaussian Nave Bayes
What about continuous features?
2
One Dimensional Continuous Feature
Assume Gaussian class conditional
CS464
Introduction to
Machine Learning
Lecture 4
znur Tatan
Bilkent University
Administrivia
Office hours announced included in the syllabus
znur Tatan
Office: EA 429
Office Hour: By appointment
CS464
Introduction to
Machine Learning
Lecture 5
znur Tatan
Bilkent University
Administrivia
Midterm date is set.
Nov 26 Tuesday 18:00 20:00 pm
HW1 is due Oct 11 5:00 pm
Well talk about projects (
CS464
Introduction to
Machine Learning
Lecture 3
znur Tatan
Bilkent University
Admistrivia
The homework 1 will be next week. It will be on
probability about 6 questions, there will be one
programming
Lexical Analyzer
Lexical Analyzer reads the source program character by character to produce tokens. Normally a lexical analyzer doesnt return a list of tokens at one shot, it returns a token when th
Concept Learning
Inducing general functions from specific training examples is a main issue of machine learning. Concept Learning: Acquiring the definition of a general category from given sample pos
CS464 Introduction to Machine Learning
Fall 2009 Homework 3 Nueral Networks Due Date: November 18, 2009 Q1) a) Design a two-input perceptron that implements the boolean function A B. b) Give the trace
CS464 Introduction to Machine Learning
Fall 2009 Homework 2 Decision Tree Learning Due Date: October 23, 2009
Q1) Give decision trees to represent the following boolean functions: A B A [B C] A XOR B
CS464 Introduction to Machine Learning
Fall 2009 Homework 1 Concept Learning Due Date: October 14, 2009
Assume that the following training examples are given: Ex 1 2 3 4 Attrb1 a a b c Attrb2 b b c b