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MIS272 – Predictive Analytics

T2 2022

Assignment 2

Executive summary                                (1 page)

Use this section to include an executive summary written for a senior business manager or similar non-technical reader.

Include your key recommendations to the business here. When presenting your recommendations, ensure you add references to specific analyses and results in the subsequent sections of your report (e.g., by means of page numbers, figure references).

Rubric reference: Executive summary and recommendations

Data exploration, pattern discovery, and preparation                                                                                                               (2 pages)

Use this section to include all your work on finding meaningful patterns in the data set as relevant to the case study using RapidMiner. This may include:

- your exploration of relevant data attributes as predictors

- your selection of an attribute as label

- your approach to dealing with missing values, errors in the dataset, etc.

- transformations you have done on the data (including any modifications on the data, any numeric normalizations, or any type conversions such as nominal to numeric and the similar)

- your data distribution analysis (e.g., using histograms or scatterplots)

- your correlation analyses using correlation matrices

- your cluster analysis

- your detection of (and discussion around) outliers

Make sure your visualizations are accompanied by relevant discussions of the insights the analyses and visualizations will/should lead to. BRING IN SCREENSHOTS OF YOUR RAPIDMINER PROCESSES AND EXPLAIN THE MAJOR FUNCTIONALITIES IF YOU DO SO…

Rubric reference: Explore, discover, and prepare data for predictive analysis

Predictive modelling                                                                           (2 page)

Use this section to show and discuss the RapidMiner predictive process/processes you have created as relevant to the case study. This may include:

- your estimation analysis workings and models

- your justification of why you chose to carry out the specific analysis with the specific data attributes

BRING IN SCREENSHOTS OF YOUR RAPIDMINER PROCESSES AND EXPLAIN THE MAJOR FUNCTIONALITIES IF YOU DO SO…

Rubric reference: Analyse data (estimation and association analysis)

Association analysis                                                                                 (1 page)

Use this section to report your findings in terms of association analysis. This may include:

- your frequent item set discovery process

- your frequent item set discovery results (evaluation) and discussion

BRING IN SCREENSHOTS OF YOUR RAPIDMINER PROCESSES AND EXPLAIN THE MAJOR FUNCTIONALITIES IF YOU DO SO…

Rubric reference: Analyse data (estimation and association analysis)

Model evaluation and improvement                                                                                                              (1 page)

Use this section to report your evaluation procedures and results in RapidMiner. Also, report any steps you have taken to improve the performance of your model/s. This may include:

- your evaluation procedure (e.g., hold-out or resampling) for any of the analysis cases you have included in the previous section

- your comparative analysis on the evaluations of different predictive models or different evaluation procedures you have developed (e.g., any performance improvements you may have achieved by trying different pre-processing, outlier removal, validation, or feature selection tasks)

BRING IN SCREENSHOTS OF YOUR RAPIDMINER PROCESSES AND EXPLAIN THE MAJOR FUNCTIONALITIES IF YOU DO SO…

Rubric reference: Evaluate and improve analytics solutions