Posted: February 7th, 2015

Final Exam

Paper, Order, or Assignment Requirements

I will be attaching the textbook for reference. Please follow the instructions below. Thank you

For this order, your answers will be graded on the depth of understanding demonstrated in your discussion. On questions where I ask you to discuss, little credit will be given for simply repeating what the authors have said. Answer the questions using a word processor. Make sure that you use a spelling checker. Cite all references used including our textbook. This includes any information that you get from the Web. DO NOT FORGET to enclose any direct quotes in quotation marks and use the APA style for all citations and references.

Your submission will be evaluated by the following criteria.
1. Correctness of your answers.
2. Your ability to provide critical thoughts; and the soundness of these critical thoughts.
3. Technical depth and the comprehensiveness of your answers.
4. Formatting and proper use of quotations, citations, and the APA format.

Here are the questions:

The leukemia dataset proposed by Golub, et al., 1999 has been extensively used to test machine learning algorithms. Information about the dataset along with a copy of the original paper published in Science that describes the dataset can be found at:

http://www-genome.wi.mit.edu/cgi-bin/cancer/publications/pub_paper.cgi?mode=view&paper_id=43

1. Describe the class prediction problem that the authors are addressing.

2. Describe the datasets used for experiments on the class prediction problem.

3. Describe the class discovery problem that the authors are addressing.

4. What are the arguments for using a neighborhood analysis approach for AML-ALL class predication? Indicate if you agree or disagree with their approach, and provide justifications.

5. What was the overall prediction success rate with cross validation shown in the paper? Comment on the meaning of this result.

6. What are the arguments for using a self-organizing map approach for class discovery? Indicate if you agree or disagree with their approach, and provide justifications.

7. How do you evaluate the overall quality of the paper? Are there some potential improvements that can be made to improve the performances on the class prediction and class discovery techniques described in the paper?

8. What will be your approach(es) if you intend to solve the class prediction/discovery problem discussed in the paper? How do you expect the pros and cons of your approach? (Note: you don’t have to implement your approach(es) to answer this question.)

http://www.4shared.com/office/89TVTOU9ba/Artificial_Intelligence_A_Mode.html