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 exploring the data set and preparing it for further processing in RapidMiner. Also, 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 section may include:
- your selection of relevant data attributes as predictors
- your selection of an attribute as label
- your ways of dealing with missing values
- transformations you have done on the data (can be any textual 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 correlations analyses using correlation matrices
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 (1 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 classification/estimation/clustering analysis/association rule analysis workings
- your justification of why you chose to carry out that specific analysis (e.g., why classification and not estimation and what this would mean in the context of the case study in the assignment)
BRING IN SCREENSHOTS OF YOUR RAPIDMINER PROCESSES AND EXPLAIN THE MAJOR FUNCTIONALITIES IF YOU DO SO…
Rubric reference: Analyse data with predictive models
Model evaluation and improvement (2 pages)
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…
- 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 you have created (if you have created more than one model, e.g., decision trees as well as K-NN)
- any performance improvements you may have achieved by trying different evaluation procedures (e.g., hold-out vs. resampling)
- any performance improvements you may have achieved using ensemble techniques (e.g., stacking)
BRING IN SCREENSHOTS OF YOUR RAPIDMINER PROCESSES AND EXPLAIN THE MAJOR FUNCTIONALITIES IF YOU DO SO…
Rubric reference: Evaluate and improve analytic solutions
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