Reference no: EM132969440 , Length: word count:2000

Question: You are required to access a large data set and apply the CRISP-DM methodology to meaningfully clean, transform, analyse and evaluate it. As part of this process, you are required to subsequently apply one or more machine learning technique(s) of your choice to perform classification, association, numerical prediction and/or clustering tasks (or combinations there of).

You will present the outcome of the above tasks in the form of a technical report containing the five sections listed in Table 1.

Section	Weighting	Recommended Pages per Section
1. Introduction and Business Context	0.1	1
2. Data Selection and Pre-Processing	0.3	3
3. Machine Learning Method(s) and their Implementation	0.3	3
4. Evaluation of Results	0.2	2
5. Discussion	0.1	1

As shown in Table 1, a page limit of 10 pages is recommended. The report, in total, however, must not exceed 13 pages (excluding title page, contents page, references, bibliography and appendices) with a minimum font size of 10 pitch. A penalty of a single grade will be incurred if you exceed the 13-page limit. Further information (supporting experimental results) can be added as appendices.

You are free to select the style of the report (i.e., section headings and format, etc.) although it must obviously address the content listed in Table 1.

You are expected to submit the following electronic files to the designated repository by the submission deadline:
- Training, validation and test sets (before and after pre-processing). Note that if cross-validation is used, only the training and test sets are required;

The remainder of this section provides you with detailed requirements for each area of content.

Attachment:- CRISP-DM methodology.rar