COMP3425 Data Mining 代写

COMP3425 Data Mining 代写，以前完成的啦，如果有需要写的直接联系我们

COMP3425 Data Mining S1 2018

Assignment 1

Maximum marks 100

Weight 20% of the total marks for the course

Length

Maximum of 8 pages and maximum of 2,500 words, in both

cases excluding cover sheet, bibliography and appendices.

Layout

A4 margin, at least 11 point type size. Use of typeface, margins

and headings consistent with a professional style.

Submission deadline 5:00pm, Friday, 16 March

Submission mode Electronic, PDF via Wattle

Estimated time 15 hours

Penalty for lateness 100% after the deadline has passed

First posted: 19

th

Feb, 9am

Last modified: 19

th

Feb, 9am

Questions to: Wattle Discussion Forum

This assignment specification may be updated to reflect clarifications and modifications

after it is first issued.

It is strongly suggested that you start working on the assignment right away. You can submit

as many times as you wish. Only the most recent submission at the due date will be

assessed.

In this assignment, you are required to submit a single report comprising your answers to

set questions in the form of a PDF file. You may also attach supporting information

(appendices) as one or more separate PDF files. Appendices will not be marked but may be

treated as supporting information to your answers.

This is a single-person assignment and should be completed on your own. Make certain you

use quality information and that you carefully reference all the material that you use. Any

material that you wish to quote must have the source clearly referenced. It is unacceptable

to present any portion of another author’s work as your own. Anyone found doing this, from

whatever source, will be will be penalised in marks and, in addition, CECS procedures for

plagiarism will apply.

Task

The Australian Computer Society Code of Professional Conduct 2014 is expected to be

applied by all Computing Professionals in Australia. It sets out six values but stresses the primacy of the public interest as the overriding value. In 2017, the US Branch of the

Association for Computing Machinery (ACM), recognizing the ubiquity and far-reaching

impact of algorithms in daily lives, issued a Statement on Algorithmic Transparency and

Accountability incorporating seven Principles designed to address potential harmful social

discrimination due to bias. These two documents are provided with this assignment

specification and you must read them closely.

You must also read the paper, Clarke R. (2018) “Guidelines for the Responsible Application of

Data Analytics” Forthcoming, Computer Law & Security Review 34, 3 (Jul-Aug 2018) , that is

provided with this assignment specification and hereafter referred to as the Guidelines.

You are to consider the application of the ACS code of conduct, the 7 US ACM Principles and

Clarke’s Guidelines to the following fictitious precipitation events scenario.

Precipitation Events Scenario (from Clarke R. (2016) “Big Data, Big Risks” Information Systems

Journal 26, 1 (January 2016) 77-90, PrePrint at http://www.rogerclarke.com/EC/BDBR.html)

Historical rainfall data is acquired from many sources, across an extended period,

and across a range of geographical locations. The collectors, some of them

professionals but most of them amateurs, used highly diverse collection methods

and frequencies, with little calibration and few controls. The data is consolidated

into a single collection. A considerable amount of data manipulation is necessary,

including the interpolation of data for empty cells, and the arbitrary disaggregation

of long-period data into the desirable shorter periods. An attempt to conduct a

quality audit against such sources as contemporaneous newspaper reports proves to

be too expensive, and is curtailed.

Analytical techniques are applied to the data. Confident conclusions are reached

about historical fluctuations and long-term trends. Climate-change sceptics point to

the gross inadequacies in the database, and argue that climate-change proponents,

in conducting their crusade, have played fast and loose with scientific principles.

You must answer the following questions, clearly indicating which question you are

answering within your submission. The page lengths given for each question here are for

guidance only; the page lengths for the overall assignment prescribed elsewhere are

mandatory.

Question 1. (1 page) Consider the ACS code of conduct. For each of the six values and their

sub-parts, discuss whether the value was demonstrated in the scenario and to what extent.

If you consider any value largely irrelevant to the scenario, then a very brief reason for this

assessment is sufficient.

Question 2. (1/2 page) Consider the 7 US ACM Principles. Looking closely at Principle 1,

Awareness, discuss how this principle is applied (or not) in the scenario and identify any

“potential harm” that might have ensued. Question 3. (4 pages) One-by-one, consider every numbered guideline in Table 2 of Clarke’s

Guidelines for the responsible application of data analytics and identify, with justification,

whether the guideline is applicable or irrelevant to the scenario. If you argue that the

guideline is applicable in principle, but needs to be adapted to be more obviously applicable,

then propose a suitable re-phrasing of the guideline. For clarity and brevity, you may choose

to present your answer as a table, reusing the structure and numbering of Table 2, but

without repeating the text of table 2.

Question 4. (1 page) (a) Choose any single, numbered guideline (e.g. guideline 3.3) in Table

2 of the Guidelines that you consider to have been disregarded in the scenario, and discuss

how the failure to consider the guideline could have contributed to the response of the

“Climate-change sceptics” to the conclusions drawn from the analytic work of the scenario. (b) In

addition, identify any other potential consequences that could have occurred due to the failure to

consider that same guideline. For this purpose, the consequences you identify are not necessarily

explicit within the scenario description. You might find it helpful to think of this activity as

contributing to a risk assessment process prior to your hypothetical involvement in the analysis work

of the scenario.

General Comments

An abstract or executive summary is not required. A cover sheet is optional and does not contribute

to the page count, but your report must have a clearly identified title and author on the first page

after any cover sheet. The author must be identified by both name and University U-number.

No particular layout is specified, but you should follow a professional style and use no smaller than

11 point typeface and stay within the maximum specified page count and the maximum specified

word count. Page margins, heading sizes, paragraph breaks and so forth are not specified but a

professional style must be maintained. Text beyond the page limit or word count limit will be treated

as non-existent. Appendices may be used and do not contribute to the page count, but appendices

might be only quickly scanned or used for reference and will not be specifically marked.

You should properly attribute the source documents provided for your assignment (but not this

assignment specification itself) and any other reference materials you choose to use. No particular

referencing style is required. However, you are expected to reference conventionally, conveniently,

and consistently. Your references should be sufficient to unambiguously identify the source, to

describe the nature of the source, and also to retrieve the source in online and (if possible)

traditional publisher formats.

An assessment rubric is provided. The rubric will be used to mark your assignment. You are advised

to use it to supplement your understanding of what is expected for the assignment and to direct

your effort towards the most rewarding parts of the work.

Your assignment submission will be treated confidentially, but it will be available to ANU

staff involved in the course for the purposes of marking. Assessment Rubric

This rubric will be used to mark your assignment. You are advised to use it to supplement your understanding of what is expected for the assignment and to

direct your effort towards the most rewarding parts of the work. Your assignment will be marked out of 100, and marks will be scaled back to contribute to

the defined weighting for assessment of the course.