Machine Learning
Overview of probability
Hamid Beigy
Sharif University of Technology
Fall 1393
Hamid Beigy (Sharif University of Technology)
Machine Learning
Fall 1393
1 / 12
Probability
The probability of an event is the fraction of times that an event o
Linear & nonlinear classiers
Machine Learning
Hamid Beigy
Sharif University of Technology
Fall 1393
Hamid Beigy (Sharif University of Technology)
Linear & nonlinear classiers
Fall 1393
1 / 34
Table of contents
1
Introduction
2
Linear classiers through ori
Machine Learning
1
Decision Trees
Machine Learning
When to Consider
Using Decision Trees
2
Instances Describable by Attribute-Value Pairs
Target Function Is Discrete Valued
Disjunctive Hypothesis May Be Required
Possibly Noisy Training Data
Examples
Equip
Multi-class Classiers
Hamid Beigy (Sharif University of Technology)
Machine Learning
Hamid Beigy
Sharif University of Technology
Fall 1393
Multi-class Classiers
Fall 1393
1/1
Table of contents
Hamid Beigy (Sharif University of Technology)
Multi-class Clas
Linear Regression
Machine Learning
Hamid Beigy
Sharif University of Technology
Fall 1393
Hamid Beigy (Sharif University of Technology)
Linear Regression
Fall 1393
1 / 38
1
Introduction
2
Linear regression
3
Model selection
4
Sample size
5
Maximum likeliho
Classication based on Bayes decision theory
Machine Learning
Hamid Beigy
Sharif University of Technology
Fall 1393
Hamid Beigy (Sharif University of Technology)
Classication based on Bayes decision theory
Fall 1393
1 / 41
1
Introduction
2
Bayes decision t
Machine Learning
Introduction
Hamid Beigy
Sharif University of Technology
Fall 1393
Hamid Beigy (Sharif University of Technology)
Machine Learning
Fall 1393
1 / 15
Table of contents
1
What is machine learning?
2
Types of machine learning
3
Outline of cour
Classication based on Bayes decision theory
Machine Learning
Hamid Beigy
Sharif University of Technology
Fall 1393
Hamid Beigy (Sharif University of Technology)
Classication based on Bayes decision theory
Fall 1393
1 / 70
1
Introduction
2
Bayes decision t
Machine Learning
Assignment 4
Due date: 1393/10/13
1- Explain why the perceptron cost function is a continuous piecewise linear function.
2-
A) Consider a 2D space or x1x2 plane. What is the VC dimension of each of the
shapes of the list below where point
Machine Learning
Fall 2014
Homework 2
Name:
Hello and welcome to the machine learning second homework. The aim of this assignment
is to make you more acquainted with Bayesian decision theory and parametric methods for
density estimation. We encourage you
Machine Learning
Fall 2014
Quiz 1
Name:
1. (10 points) Consider we have a two-class (1 , 2 ) classication task:
P (1 ) = P (2 ) = 0.5
1
p(x|1 ) = exp(x 1)2 )
1
p(x|2 ) = exp(x2 )
Let L be the following loss matrix:
L=
0 e
e1 0
Design a classier that minim
Machine Learning
Fall 2014
Free Exam
Name:
1. (13 points) Let max (x) be the state of nature for which P (max |x) >= P (i |x) for all
i (i = 1, 2, c).
(a) Show that P (max |x) >=
1
c
(b) Show that for the minimum error rate decision rule the average proba
Machine Learning
1
Computational
Learning Theory
Machine Learning
Introduction
2
Computational learning theory
Is it possible to identify classes of learning problems that are inherently easy or difficult?
Can we characterize the number of training exampl
Machine Learning
1
Evaluation of
Hypotheses
Machine Learning
Classifier Evaluation [1]
2
Machine Learning algorithms induce classifiers that depend on the training set, and
there is a need for statistical testing to
Asses the expected performance of a cla
Machine Learning
1
Ensemble Learning
Machine Learning
Introduction
2
In our daily life
Asking different doctors opinions before undergoing a major surgery
Reading user reviews before purchasing a product
There are countless number of examples where we con