3 Generate test design

3.4 Output Model description

o Activities - Describe any characteristics of the current model that may be useful for the future. Give a detailed description of the model and any special features.

o Activities - State conclusions regarding patterns in the data (if any); sometimes the model reveals important facts about the data without a separate Assessment process (e.g. that the output or conclusion is duplicated in one of the inputs).

Assessment Name Weighting Alignment with Unit and Course Data Mining & BI Report 25% ULO1, ULO2, ULO3, ULO4 Due Date and Time Report (10%): Week 11, Friday, 02 October 2020, 11:59 pm via Moodle. Presentation and QA Session (15%): Week 12 In Class. Assessment Description In this assessment, the students will extend their previous work from assessment A3 Business case understanding. Here, the students have to submit a report of the data mining process on a real-world scenario and a presentation and QA Session will be held based on the report written. The report will consist of the details of every step followed by the students. Detailed Submission Requirements Cover Page Title Group members . Introduction Importance of the chosen area Why this data set is interesting What has been done so far Which can be done Description of the present experiment 1. Data preparation and Feature extraction: 1.1 Select data Task Select data 1.2 Clean data o Task Clean data Output Data cleaning report O 1.3 Construct datal feature extraction Task Construct data Output Derived attributes Activities: Derived attributes Add new attributes to the accessed data Activities Single-attribute transformations O Assessment Name Weighting Alignment with Unit and Course Data Mining & BI Report 25% ULO1, ULO2, ULO3, ULO4 Due Date and Time Report (10%): Week 11, Friday, 02 October 2020, 11:59 pm via Moodle. Presentation and QA Session (15%): Week 12 In Class. Assessment Description In this assessment, the students will extend their previous work from assessment A3 Business case understanding. Here, the students have to submit a report of the data mining process on a real-world scenario and a presentation and QA Session will be held based on the report written. The report will consist of the details of every step followed by the students. Detailed Submission Requirements Cover Page Title Group members . Introduction Importance of the chosen area Why this data set is interesting What has been done so far Which can be done Description of the present experiment 1. Data preparation and Feature extraction: 1.1 Select data Task Select data 1.2 Clean data o Task Clean data Output Data cleaning report O 1.3 Construct datal feature extraction Task Construct data Output Derived attributes Activities: Derived attributes Add new attributes to the accessed data Activities Single-attribute transformations O