BUS5650 Business applications of neural networks - Semester 2 , 2007

Clayton

• Chung-Hsing Yeh

Clayton

• Lin Chen

Prerequisites

Before attempting this unit you must have satisfactorily completed

BUS9530 (Business Systems B) or equivalent quantitative subject, or equivalent.

Relationships

BUS5650 is an elective unit in the Master of Business Systems Degree.

It is a prerequisite/corequisite that Before attempting this unit you must have satisfactorily completed

BUS9530 (Business Systems B) or equivalent quantitative subject, or equivalent.

You may not study this unit and

BUS3650

in your degree.

Unit leader

Lecturer(s) :

Tutor(s) :

This is an on-campus unit. Students are required to attend lectures and tutorials (compulsory and attendance will be taken). The unit is taught in six modules, supported by tutorial exercises and additional reading material. It is expected that students spend at least additional 4 hours per week to study the lecturing material and prepare for  tutorial exercises. Solutions to the tutorial exercises will be available on the unit MUSO site one day after the tutorial. 

Communication, participation and feedback

Monash aims to provide a learning environment in which students receive a range of ongoing feedback throughout their studies. You will receive feedback on your work and progress in this unit. This may take the form of group feedback, individual feedback, peer feedback, self-comparison, verbal and written feedback, discussions (on line and in class) as well as more formal feedback related to assignment marks and grades. You are encouraged to draw on a variety of feedback to enhance your learning.

It is essential that you take action immediately if you realise that you have a problem that is affecting your study. Semesters are short, so we can help you best if you let us know as soon as problems arise. Regardless of whether the problem is related directly to your progress in the unit, if it is likely to interfere with your progress you should discuss it with your lecturer or a Community Service counsellor as soon as possible.

Unit Schedule

Week	Topic	Key dates
1	Introduction to Neural Networks and their Business Applications
2	Introduction to Neural Networks and their Business Applications
3	Perceptrons
4	Perceptrons
5	Multilayered Networks (Backpropagation)
6	Multilayered Networks (Backpropagation)	Mid-semester test
7	Multilayered Networks (Backpropagation) Case Studies	Assignment proposal due
8	Self-organisation
9	Self-organisation
10	Data Mining
Mid semester break
11	Data Mining
12	Other Intelligent Techniques
13	Review Session	Assignment due

Prescribed text(s) and readings

Kate A. Smith, Introduction to Neural Networks and Data Mining for Business Applications, Eruditions Publishing, Emerald, 1999.

This text book is available from the Monash University Book Shops. Availability from other suppliers cannot be assured.

Recommended text(s) and readings

Recommended readings for each lecture module will be made available during lectures. These readings are either available from the on-line Monash Library system or placed in folders available in the Hargrave-Andrew Library for photocopying.

Equipment and consumables required or provided

On-campus students and those studying at supported study locations may use the facilities available in the computing labs. Information about computer use for students is available from the ITS Student Resource Guide in the Monash University Handbook. You will need to allocate up to 3 hours per week for use of a computer.

Study resources

Study resources we will provide for your study are:

Study resources we will provide for your study are:

• Weekly detailed lecture notes outlining the learning objectives, discussion of the content, required readings and  exercises;
• Weekly tutorial or laboratory tasks and exercises with sample solutions provided one to two days later;
• Assignment specifications and sample solutions;
• A sample examination and suggested solutions;
• This Unit Guide outlining the administrative information for the unit;
• The unit web site on MUSO, where resources outlined above will be made available.

Library access

The Monash University Library site contains details about borrowing rights and catalogue searching. To learn more about the library and the various resources available, please go to http://www.lib.monash.edu.au.  Be sure to obtain a copy of the Library Guide, and if necessary, the instructions for remote access from the library website.

Monash University Studies Online (MUSO)

All unit and lecture materials are available through the MUSO (Monash University Studies Online) site. You can access this site by going to:

1. a) https://muso.monash.edu.au or
2. b) via the portal (http://my.monash.edu.au).

Click on the Study and enrolment tab, then the MUSO hyperlink.

In order for your MUSO unit(s) to function correctly, your computer needs to be correctly configured.

For example :

• MUSO supported browser
• Supported Java runtime environment

For more information, please visit

http://www.monash.edu.au/muso/support/students/downloadables-student.html

You can contact the MUSO Support by: Phone: (+61 3) 9903 1268

For further contact information including operational hours, please visit

http://www.monash.edu.au/muso/support/students/contact.html

Further information can be obtained from the MUSO support site:

http://www.monash.edu.au/muso/support/index.html

Unit assessment policy

The unit is assessed with one assignment (30%), one one-hour test (20%) and a two-hour closed book examination (50%). To pass the unit you must:

• attempt the assignment, the test, and the examination
• achieve no less that 40% of the possible marks in the exam
• achieve no less than 50% of possible marks

Assignment tasks

• Assignment Task

  Title :

  Solving a business problem using neural networks

  Description :

  In this assignment, you will be applying what you have learnt about neural networks and the backpropagation learning algorithm to a forecasting, prediction or classification problem of your choice.

  Weighting :

  30%

  Criteria for assessment :

  Due date :

  15 October 2007

Examinations

• Examination

  Weighting :

  20%

  Length :

  1 hour

  Type ( open/closed book ) :

  Closed book

  Remarks ( optional - leave blank for none ) :

  Mid-semester test during week 6 lecture

• Examination

  Weighting :

  50%

  Length :

  2 hours

  Type ( open/closed book ) :

  Closed book

  Remarks ( optional - leave blank for none ) :

  Final examination

Assignment submission

Assignments will be submitted by paper submission to Assignment Box, Building 63. The assignment must be accompanied with the appropriate cover sheet correctly filled out and attached. Do not email submissions. The due date is the date by which the submission must be received.

Assignment coversheets

The assignment cover sheet can be downloaded from the Faculty of IT website:

http://www.infotech.monash.edu.au/resources/student/

Due dates and extensions

The due dates for the submission of assignments are given in the previous section. Please make every effort to submit work by the due dates. It is your responsibility to structure your study program around assignment deadlines, family, work and other commitments. Factors such as normal work pressures, vacations, etc. are seldom regarded as appropriate reasons for granting extensions. Students are advised to NOT assume that granting of an extension is a matter of course.

Requests for extensions must be made to the unit lecturer or your tutor at least two days before the due date. You will be asked to forward original medical certificates in cases of illness, and may be asked to provide other forms of documentation where necessary. A copy of the email or other written communication of an extension must be attached to the assignment submission.

Late assignment

Assignments received after the due date will be subject to a penalty of 5% per day, including weekends. Assignments received later than one week (seven days) after the due date will not normally be accepted.

Return dates

Students can expect assignments to be returned within two weeks of the submission date or after receipt, whichever is later.

Assessment for the unit as a whole is in accordance with the provisions of the Monash University Education Policy at:

http://www.policy.monash.edu/policy-bank/academic/education/assessment/

We will aim to have assignment results made available to you within two weeks after assignment receipt.

Plagiarism, cheating and collusion

Plagiarism and cheating are regarded as very serious offences. In cases where cheating  has been confirmed, students have been severely penalised, from losing all marks for an assignment, to facing disciplinary action at the Faculty level. While we would wish that all our students adhere to sound ethical conduct and honesty, I will ask you to acquaint yourself with Student Rights and Responsibilities (http://www.infotech.monash.edu.au/about/committees-groups/facboard/policies/studrights.html) and the Faculty regulations that apply to students detected cheating as these will be applied in all detected cases.

In this University, cheating means seeking to obtain an unfair advantage in any examination or any other written or practical work to be submitted or completed by a student for assessment. It includes the use, or attempted use, of any means to gain an unfair advantage for any assessable work in the unit, where the means is contrary to the instructions for such work. 

When you submit an individual assessment item, such as a program, a report, an essay, assignment or other piece of work, under your name you are understood to be stating that this is your own work. If a submission is identical with, or similar to, someone else's work, an assumption of cheating may arise. If you are planning on working with another student, it is acceptable to undertake research together, and discuss problems, but it is not acceptable to jointly develop or share solutions unless this is specified by your lecturer. 

Intentionally providing students with your solutions to assignments is classified as "assisting to cheat" and students who do this may be subject to disciplinary action. You should take reasonable care that your solution is not accidentally or deliberately obtained by other students. For example, do not leave copies of your work in progress on the hard drives of shared computers, and do not show your work to other students. If you believe this may have happened, please be sure to contact your lecturer as soon as possible.

Cheating also includes taking into an examination any material contrary to the regulations, including any bilingual dictionary, whether or not with the intention of using it to obtain an advantage.

Plagiarism involves the false representation of another person's ideas, or findings, as your own by either copying material or paraphrasing without citing sources. It is both professional and ethical to reference clearly the ideas and information that you have used from another writer. If the source is not identified, then you have plagiarised work of the other author. Plagiarism is a form of dishonesty that is insulting to the reader and grossly unfair to your student colleagues.

Register of counselling about plagiarism

The university requires faculties to keep a simple and confidential register to record counselling to students about plagiarism (e.g. warnings). The register is accessible to Associate Deans Teaching (or nominees) and, where requested, students concerned have access to their own details in the register. The register is to serve as a record of counselling about the nature of plagiarism, not as a record of allegations; and no provision of appeals in relation to the register is necessary or applicable.

Non-discriminatory language

The Faculty of Information Technology is committed to the use of non-discriminatory language in all forms of communication. Discriminatory language is that which refers in abusive terms to gender, race, age, sexual orientation, citizenship or nationality, ethnic or language background, physical or mental ability, or political or religious views, or which stereotypes groups in an adverse manner. This is not meant to preclude or inhibit legitimate academic debate on any issue; however, the language used in such debate should be non-discriminatory and sensitive to these matters. It is important to avoid the use of discriminatory language in your communications and written work. The most common form of discriminatory language in academic work tends to be in the area of gender inclusiveness. You are, therefore, requested to check for this and to ensure your work and communications are non-discriminatory in all respects.

Students with disabilities

Students with disabilities that may disadvantage them in assessment should seek advice from one of the following before completing assessment tasks and examinations:

• Faculty of Information Technology Student Service staff, and / or
• your Unit Coordinator, or
• Disabilities Liaison Unit

Deferred assessment and special consideration

Deferred assessment (not to be confused with an extension for submission of an assignment) may be granted in cases of extenuating personal circumstances such as serious personal illness or bereavement. Special consideration in the awarding of grades is also possible in some circumstances. Information and forms for Special Consideration and deferred assessment applications are available at http://www.monash.edu.au/exams/special-consideration.html. Contact the Faculty's Student Services staff at your campus for further information and advice.