Programming Question

Refer to attachments for details

ANL305
Association and Clustering
Tutor-Marked Assignment
July 2023 Presentation
ANL305
Tutor-Marked Assignment
TUTOR-MARKED ASSIGNMENT (TMA)
This assignment is worth 24% of the final mark for ANL305 Association and Clustering.
The cut-off date for this assignment is 20 September 2023, 2355hrs.
Up to 25 marks of penalties will be imposed for inappropriate or poor paraphrasing. For serious
cases, they will be investigated by the examination department. More information on effective
paraphrasing
strategies
can
be
found
on
https://academicguides.waldenu.edu/writingcenter/evidence/paraphrase/effective.
If your course involves programming, you are urged to read the following articles as well:
https://wiki.cs.astate.edu/index.php/Plagiarism_in_a_Programming_Context
https://www.turnitin.com/blog/plagiarism-and-programming-how-to-code-withoutplagiarizing-2
Note to Students:
Compose your report using Microsoft Office Word, and save either as .doc or .docx
(preferred).
You are to include the following particulars in your submission: Course Code, Title of the
TMA, SUSS PI No., Your Name, and Submission Date.
Use of Generative AI Tools (Allowed)
The use of generative AI tools is allowed for this assignment.
•
You are expected to provide proper attribution if you use generative AI tools while
completing the assignment, including appropriate and discipline-specific citation, a
table detailing the name of the AI tool used, the approach to using the tool (e.g. what
prompts were used), the full output provided by the tool, and which part of the output
was adapted for the assignment;
•
To take note of section 3, paragraph 3.2 and section 5.2, paragraph 2A.1 (Viva Voce)
of the Student Handbook;
•
The University has the right to exercise the viva voce option to determine the authorship
of a student’s submission should there be reasonable grounds to suspect that the
submission may not be fully the student’s own work.
•
For more details on academic integrity and guidance on responsible use of generative
AI tools in assignments, please refer to the TLC website for more details;
•
The University will continue to review the use of generative AI tools based on feedback
and in light of developments in AI and related technologies.
SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS)
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ANL305
Tutor-Marked Assignment
Customer engagement is vital for businesses across industries. Through creating meaningful
interactions and connections with customers, customer engagement could foster customer
loyalty, drive customer satisfaction, and attract new customers. Researchers found that engaged
customers are more likely to become brand advocates, provide feedback, and make repeat
purchases. There are many customer engagement strategies, and one famous strategy is
customer campaign, which is a strategic marketing initiative aimed at engaging and influencing
a specific target customer.
Suppose you are a Data Analyst of the supermarket ABC, and involved in a project which aims
to study their customer personality. You are given a relevant dataset named Customer
_campaign.csv, which contains the information of 2,209 customers of the supermarket. The
data details are shown in the following data description table. Answer the three (3) questions
to assist the study.
FIELD
DESCRIPTION
Customer’s unique identifier
ID
Customer Information
Age: integer value in [18, 74]
Age
Education level: 2n Cycle, Basic, Graduation, Master, PhD
Education
Marital status: Alone, Divorced, Married, Single, Together, Widow
Marital_Status
Customer’s yearly household income (in USD): integer value in [1730,
Income
NumKid
NumTeen
Purchasing Behavior
Recency
MntWines
MntFruits
MntFishes
MntMeat
MntSweetProds
666666]
Number of children in customer’s household: 0, 1, 2
Number of teenagers in customer’s household: 0, 1, 2
Number of days since customer’s last purchase in the supermarket
Amount spent on wine in the last 2 years: integer value in [0, 1493]
Amount spent on fruits in the last 2 years: integer value in [0, 199]
Amount spent on fishes in the last 2 years: integer value in [0, 259]
Amount spent on meat in the last 2 years: integer value in [0, 1725]
Amount spent on sweet products in the last 2 years: integer value in [0,
262]
Amount spent on gold labelled products in the last 2 years: integer value
MntGoldProds
in [0, 321]
Number of purchases made with a discount: integer value in [0, 15]
NumDealsPruchases
NumCatalogPurchases Number of purchases made using a catalogue: integer value in [0, 28]
If the customer complained in the last 2 years: 1 – Yes, 0 – No
Complain
Responses in Previous Campaigns
If the customer accepted the offer in the 1st campaign: 1 – Yes, 0 – No
AcceptedCmp1
If the customer accepted the offer in the 2nd campaign: 1 – Yes, 0 – No
AcceptedCmp2
If the customer accepted the offer in the 3rd campaign: 1 – Yes, 0 – No
AcceptedCmp3
If the customer accepted the offer in the 4th campaign: 1 – Yes, 0 – No
AcceptedCmp4
If the customer accepted the offer in the 5th campaign: 1 – Yes, 0 – No
AcceptedCmp5
Response in the Current Campaign
If the customer accepted the offer in the current campaign: 1 – Yes, 0 – No
Response
SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS)
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ANL305
Tutor-Marked Assignment
Question 1
Based on the given background and dataset details, identify a potential business problem. State
the business objective and data mining objective and appraise the suitability of using
association rule mining for solving the proposed business problem.
(8 marks)
Question 2
Import the data into the SPSS Modeler and construct an Apriori model using the following
settings (Data preparation is NOT required for Q2 before performing the following settings):
•
Measurement setting: click “Read Values” under the tab “Types”, then keep “Nominal”
fields unchanged and set the “Continuous” fields that have less than 4 different values
as Nominal or Flag accordingly.
Role setting: set field “Response” as Target, set the Nominal and Flag fields as Input,
set all other fields as None.
•
Show the screenshot of your node setting, and then link an Apriori node to the data node.
Clearly illustrate the parameter settings of your model node. Show and discuss your modelling
results and findings.
Note: for Q2, keep your answer within 2 pages.
(22 marks)
Question 3
Suppose you would like to explore more fields of the dataset and then construct another model,
answer the following questions to complete the work:
(a) Import the data file into a new data node and apply the following settings:
•
•
Measurement setting: the same as Q2.
Role setting: set field “ID” as None, “Response” as Target, and all other 21 fields as
Input.
Then link an “Audit” node to the data node and report the screenshot of the auditing
results under the tab “Audit”. Use up to 50 words to describe the results.
(5 marks)
(b) Transform all the continuous fields (i.e., fields with Role = None in Q2) into categorical
variables using the “Binning” node in the SPSS Modeler. You can select the “Equalwidth” method or the “Tiles (Equal-count)” method to complete the binning work. Report
the auditing results of the transformed fields.
Note: Each of the newly generated fields should have no more than four categories (aka
bins). You may use the same binning method (or a mixture of different binning methods)
for the fields. It is also acceptable to propose an alternative binning method if you think
SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS)
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ANL305
Tutor-Marked Assignment
the binning methods provided by the IBM SPSS Modeler are not suitable for some fields.
Justify your choices briefly.
(20 marks)
(c) Construct a new Apriori model using the transformed dataset. Report the settings of the
model node clearly. Report and analyse your modelling results, which should include:
number of the generated rules, important rules, and a summary and discussion on the
learned insights by comparing them to the findings in Q2.
Note: to illustrate the modelling results, you may only need to show those rules that may
contain useful patterns. It is not necessary to display all the generated rules.
(40 marks)
(d) Propose two (2) deployment suggestions referring to the business problem you have
proposed in Q1 (use up to 100 words).
(5 marks)
Report writing
Your writing should be succinct but not at the expense of excluding relevant details. Highlight
only the points that are relevant to your discussion. Use plain and simple language. Some
questions may not come with absolutely right or wrong answers. For such questions, you have
the liberty to express your views about the problem. However, your points have to be
supported by evidence and good reasoning. It’s the quality and not the length that counts.
Make sure you follow the report guidelines and style specified in this assignment.
Make sure you indicate your name and student number on the cover page of the report.
The topics in the main report should be presented in the order according to the sequence of
the tasks/questions listed in the assignment; that is, in the order of (a), (b), …, etc. You can
have several sub-sections within a section if you deem appropriate.
The report must be self-contained. It is important to include all relevant tables and figures in
the report as evidence to support the answers given.
The followings are some details of report format:
• Length: should not exceed 8 pages (including the relevant graphs, tables, references,
screenshots and appendices (if any), but excluding the cover page) Note: Deduct 5
marks for each extra page. Deduct maximum of 10 marks for excessive page
count.
• Font Style: Times New Roman
• Font size: 12
• Line spacing: 1.5
• Margins: 1” for the top, bottom, right and left
• Include the page number on each page
Some further suggestions:
• Ensure minimal grammatical and typographical errors
SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS)
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ANL305
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Tutor-Marked Assignment
Write clearly in plain English
Write appropriately to the context
Cite appropriate sources
Provide a reference or bibliography at the end of the main report
Include less relevant details in the Appendix
Good overall presentation of the report
—- END OF ASSIGNMENT —-
SINGAPORE UNIVERSITY OF SOCIAL SCIENCES (SUSS)
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