University : Middlesex University Dubai UniLearnO is not sponsored or endorsed by this college or university.
Subject Code : CST4040
Country : United Kingdom
Assignment Task:

Assessed learning outcome (s) 
This coursework will enable the student to: 
1. Critically evaluate concepts and current systems in the area of Data Mining. 
2. The ability to explore a topic critically and in depth by means of literature review and creative essay writing. 
3. Perform analysis of advantages and disadvantages of different system design choices.

Part A 
You are required to write a literature review essay on a DM related topic. This should involve one DM technique type, approach or methodology and one real life application area (such as “health”, “finance”, “marketing” etc). The literature review will be focused on the chosen combination (such as “DM Classification applications to Health Science”, “Clustering in Marketing applications”). Your choice of topic can be discussed and approved by the topic tutor (Miltos Petridis). It should provide a balance between breadth of coverage and depth of treatment, providing the vehicle for a technically challenging but feasible critical analysis of the background and current state-of-the-art in the area. You should research this topic primarily through refereed Journal and Conference proceeding publications and searching for credible sources on the internet. Wherever you use material derived from external sources you should provide a citation to your source, and the source should be fully referenced in a Reference list at the end of your essay. You need to use consistently a recognised referencing standard, such as the “Harvard referencing style”. 
You should give a general introduction and overview of the chosen essay topic, but you can focus on particular aspects or applications of the research area. You should discuss the motivation underlying and justifying the research on the topic of your choice. You should NOT merely provide a list of extracted material. Your views on the material you present are required. Critical evaluation of material is expected. 
The Report For this part you are required to produce a report containing the review essay for your chosen topic. The essay should contain at least an Abstract, Introduction/Overview, Main Body and Conclusions. 
Maximum length for this Part: 

You are required to perform a Data Mining analysis using IBM SPSS Modeller (or any other suitable DM tool or programming platform) on a dataset from the UCI Machine learning repository selected from the application area you selected for part A of this assignment (such as “health”, “finance”, “marketing” etc) 
For the selected dataset, you are required to perform an analysis following the standard SPSS CRISP methodology steps. 
You are required to perform the following tasks: 
1. Prepare data to import into the tool and deal with any incorrect, missing or “abnormal” values. 
2. A preliminary exploratory visualisation of the data, using the tool’s 2-D and 3-D visualisation facilities. Select from your visualisations and present and interpret them. Form any hypotheses you think appropriate and state them clearly. 
3. Perform analysis and mining of your derived dataset. You should demonstrate the use of a number 
of DM models to cover at least 2 of the following methods/modelling techniques as appropriate for each dataset: 
a. Classification 
b. Clustering 
c. Association Rule Mining 
d. Regression 
e. Case Based Reasoning 
f. Artificial Neural Networks 
For each task, you need to select the appropriate models, run and evaluate the models used and their accuracy and critically compare and contrast the knowledge mined by each task and model. 
The results of this analysis need to be presented in a report explaining all the steps of the analysis. 
The Report 
For this part, you are required to produce a report describing the work done and providing an explanation and justification for the tools and the methodology followed. The report will need to contain: 
- A short introductory section describing the methodology used 
- A section describing the preparation of the data 
- A section describing how appropriate models were selected for the analysis 
- A section describing the evaluation of the model results and the level of confidence achieved 
- A conclusion giving a critical comparison of the domain knowledge elicited by each model/task. 

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  • Posted on : April 04th, 2019
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