Reference no: EM133033163

IMAT3613 Data Mining - De Montfort University

Organics Data Set Report Assignment

Learning outcome 1: To discuss what is meant by the term data mining, to be able to express a business problem within a data mining framework and identify an appropriate target variable.

Learning outcome 2: To be able to identify necessary prequisites for the application of a data mining framework and discuss the limitations of data mining methods with regard to data and methods in the context of the business problem.

Learning outcome 3: To describe and analyse the organisational structure of large data sets to facilitate effective data mining and to be able to correctly interpret and critically evaluate the results to make informed decisions within a data mining framework

Learning outcome 4: To be express the data mining framework for a particular business problem through the correct application of data mining tools.

Learning outcome 5: To interpret the results produced from data mining tools and evaluates the effectiveness of data mining methods and where necessary making appropriate recommendations for use in the virtuous cycle of data mining.

Data Mining Report A Patchwork Assignment

Structure of the coursework

The coursework is an individual piece of assessment, requiring you to analyse the ORGANICS dataset within SAS Enterprise Miner or Weka, using the directed data mining techniques covered in the IMAT3613 module, and detailing your results, interpretations, conclusions and recommendations in a well-structured technical report. You are provided with:

- This Brief
- A sample of data from the ORGANICS dataset is shown in Appendix A.
- The ORGANICS dataset contains 10,000 observations and 13 variables. The variables in the dataset are shown in Appendix B.
- The coursework will be assessed according to the marking grid in Appendix C
- Self/Peer Assessment Rubric Appendix D
- Template Report in Appendix E

Attachment:- Data Mining -Assignment Brief.rar