CSE 802, Spring 2012, Homework 2 solutions
DHS, Q7
(a) Decision boundary: x = .
1
dx
= E1
b 1 + (x a1 )/b)2
(a1 )/b
1 dy
= E1
1 + y2
tan1 ( a1 )/b) = E1
2
= a1 +
b
tan(E1 )
Note that classifying a pattern that is actually in 1 as if it where in 2 refer
CSE 802: Homework 1
Due: Jan 17, 2012
Chapter 1 of DHS book introduced an example of a pattern classification system to
separate sea bass from salmon. Along the same lines, consider the following two
classification problems:
(a) A fruit company packages f
Homework 2
CSE 802 - Pattern Recognition and Analysis
Instructor: Dr. Arun Ross
Due Date: February 18, 2014
Note:
1. You are permitted to discuss the following questions with others in the class. However, you must write
up your own solutions to these ques
Homework 2
CSE 802, Spring 2012
Due: Jan 31, 2012
1. Solve the following problems from Chapter 2 of the text book.
7, 12, 13, 27, 31
Please note that the problem numbers provided in the assignment questions correspond to the printed second edition of the
Homework 1
CSE 802: Pattern Recognition and Analysis
Instructor: Dr. Arun Ross
Due Date: Jan 28, 2014
Note: You are permitted to discuss the following questions with others in the class. However, you must write
up your own solutions to these questions. An
Homework 1
CSE 802: Pattern Recognition and Analysis
Instructor: Dr. Arun Ross
Due Date: February 8, 2016
Note: You are permitted to discuss the following questions with others in the class. However, you must write
up your own solutions to these questions
Williams et al. Anim Biotelemetry (2015) 3:45
DOI 10.1186/s40317-015-0077-0
Open Access
RESEARCH
Can accelerometry be used
todistinguish betweenflight types insoaring
birds?
H.J.Williams1*, E.L.C.Shepard1, O.Duriez2 andS.A.Lambertucci3
Abstract
Background
LEARNING TO PLAY CHESS USING
REINFORCEMENT LEARNING WITH
DATABASE GAMES
Henk Mannen
supervisor: dr. Marco Wiering
MASTERS THESIS COGNITIVE ARTIFICIAL INTELLIGENCE
UTRECHT UNIVERSITY
OCTOBER 2003
Of chess it has been said that life is not long enough for
i
Imperial College London
arXiv:1509.01549v1 [cs.AI] 4 Sep 2015
Department of Computing
Girae: Using Deep Reinforcement Learning to Play Chess
by
Matthew Lai
Submitted in partial fullment of the requirements for the MSc Degree in
Advanced Computing of Imper
Homework 4
CSE 802 - Pattern Recognition and Analysis
Instructor: Dr. Arun Ross
Due Date: April 29, 2015
Note: You are permitted to discuss the following questions with others in the class. However, you
must write up your own solutions to these questions.
Name: Practice Quiz - 1
CSE 802 - Pattern Recognition and Analysis
Posted on: February 11, 2014
1. [6 points] Briey explain the following terms with the appropriate formulae: (a) Bayes Risk;
(b) Bayes Rule.
2. Consider a two-category one-feature classicat
Homework 3
CSE 802, Spring 2012
Due: Feb 14, 2012
1. Let = Probability of Heads of a fair coin. Suppose the coin has
been tossed n times. Let nH be the number of times the coin turned
up heads.
(a) Show that the maximum likelihood estimate of is M LE =
nH
Homework 5
CSE802, Spring 2012
Due: March 15, 2012
(1) (40 points) Decision Tree
Evaluate the performance of the Decision Tree classifier on iris dataset using 10-fold cross-validation.
Use the MATLAB version of Decision Tree (classregtree).
(a) Report th
Homework 6
CSE 802, Spring 2012
Due: March 27, 2012
For the problems that involve coding, we expect you to give a report on
what you did and the results you got. Please send you codes to the TA
(bucakser@msu.edu) with an email.
1. (35 points) Evaluate the
Homework 7
CSE802, Spring 2012
Due: April 12, 2012
For the problems that involve coding, we expect you to give a report on what you did and the
results you got. Please send you codes to the TA (bucakser@msu.edu) with an email.
Problem 1
Write a program to
HW3 Sample Solutions
1:
(a) We are given that = prob( Heads ) and number of heads is nH , so the number of
tails is nT = n nH . Let's denote the "Head" outcome as x = 1 , and "Tail" outcome as
x = 0 . So,
n
l ( ) = log likelihood of = ln p ( xi / )
(1)
i
Homework 4
CSE 802, Spring 2012
Due: Feb 27, 2012
1.
(a) Compute the 2 x 2 scatter matrix S for this data
n
S = (x j x )(x j x ) , where x j is the j-th sample (row) and x is the mean vector that is
T
j =1
calculated by using all the samples. Under these
Homework 5
CSE 802, Spring 2012
Due: March 15, 2012
1.
% x is the data matrix, i.e. 150x4
% y is a cell structue of labels (string values)
for i=1:10
ind=randperm(150);
x2=x(ind(1:135),:);
ys2=ys(ind(1:135);
x3=x(ind(136:end),:);
ys3=ys(ind(136:end);
t2=c
CSE802
04/09/2012
HW 6 Solutions
Thanks to Mehrdad Mehdavi who has shared his solutions and template with us. This
answer key is a modied version of his assignment.
Problem 1
(a)
One versus Rest
*
accuracy =
1.00
1.00
0.933
0.86
1.00
1.00
0.86
1.00
0.86
0
VeggieVision: A Produce Recognition System
R. M. Bolle J. H. Connell N. Haas R. Mohan G. Taubin
IBM T.J. Watson Research Center, PO Box 704, Yorktown Heights, NY 10598
ABSTRACT
In this paper, we present a trainable produce recognition system for
supermark