IS5152 Decision Making Technologies

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IS5152 Decision Making Technologies

Semester
2, 2010/11.

Tuesdays
,

6.30
-
8.30 pm
,
COM1/204.

Instructor: Dr. Rudy Setiono

Contact:
rudys@comp.nus.edu.sg
,


disrudy@nus.edu.sg

Office: COM2 04
-
13

IS5152 Decision Making Technologies


Course objective:
to introduce students to decision making technologies
that can support decision making in the financial, operational, marketing and
other strategic areas.


Description:
Over the past two decades, increasing research efforts have
been directed at finding new machine learning (ML) techniques for decision
making and their possible application in solving practical problems. ML
techniques such as artificial neural network methods have been proven to be
powerful tools for business decision making. Among the application
problems where ML techniques outperform traditional decision making
methods such as statistical methods are credit rating, bankruptcy analysis,
foreign exchange rate predictions and many others.


IS5152 Decision Making Technologies


Topics covered:

The techniques covered in this course include neural networks for
classification/regression/clustering, genetic algorithm for optimization,
decision tree methods, support vector machine, data envelopment
analysis and data mining.


Journal articles that present new techniques for decision making and/or
describe successful application of the existing methods in solving
practical problems will be discussed in class.


IS5152 Decision Making Technologies

This course requires the students to have some background knowledge in:


Calculus


Simple linear algebra


Basic probability and statistics

No

computer programming skill is required.



IS5152 Decision Making Technologies

Tentative

schedule:


Week 1

January 11, 2011

Introduction and class administration

Week 2

January 18, 2011

Decision making under uncertainty

Week 3

January 25, 2011

Optimization

and decision making

Week

4

February

1, 2011

Support vector machines

Week 5

February

8, 2011

Decision making with multiple objectives

Week 6

February 15, 2011

Data envelopment analysis

February 22,
2011

No lecture. Mid
-
semester

break

Week 7

March 1, 2011

Mid
-
semester exam.

Week 8

March 8, 2011

Decision making with decision trees and rules

Week 9

March

15, 2011

Neural networks for decision making (Part 1)

Week 10

March

22, 2011

Neural networks for decision making (Part 2)

Week 11

March 29, 2011

Rule generation

from neural networks

Week 12

April 5, 2011

Genetic algorithms for decision

making

Week 13

April 12, 2011

Project

presentation

IS5152 Decision Making Technologies





References:
Available in the RBR sections of Central Library and HSS
Business Library.



1.
Neural networks: A comprehensive foundation

Author:
Haykin
, Simon S

2.
Machine Learning

Author: Mitchell, Tom M

3.
Operations research : applications and algorithms

Author: Winston, Wayne L

IS5152 Decision Making Technologies

Grading:






1
.

Continual

assessment

(
50
%
)
:




Midterm

Exam

(
20
%
)





Class

project

(
30
%
)
:


o

20
%

for

the

project

work,

and


o

10
%

for

project

report

and

presentation
.

o

Projects

are

to

be

carried

out

in

teams

consisting


n

students
.


2
.

Final

exam

on

6

May

pm
:

50
%
.


Both

midterm

exam

and

final

exam

are

open
-
book

examinations
.

IS5152 Decision Making Technologies

Class project:





-
Identify

an

interesting

problem/topic

to

test

one

or

more

of

the

techniques

for

decision

making

discussed

in

class
.

-
Search/find/collect

relevant

data
.


Use

an

available

software

to

analyze

the

data
.

-
Software

will

be

provided

or

they

can

be

obtained

via

the

internet
.

-
Write

a

(max)

20

page

report
.

-
Present

the

project

in

class

(duration
:

20

minutes)
.

-
More

detailed

instructions

about

the

project

will

be

given

later

in

the

semester
.


IS5152 Decision Making Technologies






IVLE
:


1.
Do

check

IVLE

for

this

course

regularly

for

announcements,

updates,

etc
.

2.
All

lecture

materials

will

be

placed

in

the

workbin
.

3.
Message

from

Students

Against

the

Violation

of

the

Earth

(SAVE)
:


the

Office

of

Provost

had

approved

the

submission

of

all

academic

assignments

for

undergraduate

and

graduate

studies

on

double
-
sided

print

or

through

electronic

submission



you

are

encouraged

to

print

your

lecture

notes

on

both

sides

on

the

paper
.

If

possible

and

depending

on

the

layout

of

the

notes,

also

encourage

them

to

print

4

to

6

pages

on

a

side