1. Produce a report on designing a complete experimental learning framework for the thorough analysis on whether a new student can pass the module or not (based on the sample dataset). [30 marks] Sample Dataset Coursework Attendance Pass Module Coursework 2 5 4 6 7 4 5 6 5 9 6 5 Student 1 2 Student 2 0 Student 3 6 Student 4 7 Student 5 Student 6 8 Student 7 9 Student 8 2 Student 9 Student 10 1 Student 11 10 Student 12 3 Student 13 6 Student 14 7 Student 15 2 Student 16 9 Student 17 6 Student 18 5 Student 19 6 Student 20 3 Student 21 7 Student 22 6 Student 23 8 Student 24 10 Student 25 3 *? Unknown More than 80% Less than 80% 80% 80% Less than 80% 80% More than 80% More than 80% Less than 80% Less than 80% More than 80% Less than 80% 80% 80% More than 80% More than 80% Less than 80% 80% Less than 80% 80% More than 80% More than 80% More than 80% More than 80% More than 80% Asking Questions in the class Often Seldom Never Often Often Often Never Seldom Never Often Seldom Seldom Seldom Seldom Seldom Never often Never Never Often often Seldom Often Often Never Y ? ? ? N Y Y N Y N Y 7 2 2 ? 6 7 8 9 10 2 N Y ? 7 10 6 10 4 5 ? ? ? ? ? ? Report Structure The report should have the following sections: o Description of the sample dataset. Analyse in quantitative terms the characteristics of the datasets (e.g. number and type of attributes, number of instances, class distribution, etc.). (4 marks) o Brief description of the chosen learning framework and justify why it will work. (8 marks) Details of the design. Explain all the learning process (e.g. how to prepare the training and test sets, list of components...) and how learning algorithm/algorithms can be implemented to do the analysis (e.g. what the learning algorithm is, how it works with the sample dataset,.....). The goal of this section is to describe the setup of the learning framework you do in a way that anybody that reads your description is able to replicate them. (10 marks) Performance evaluation. Describe how you are going to evaluate the performance of the learning framework. (4 marks) o Conclusions. Brief summary containing the highlights of your design. (4 marks) Report Length Provide your answer in a maximum of 2 pages (font Calibri; size 11). 2. Choose a knowledge representation method for instances in Sample Dataset with justification and show how student 1 and student 5 could be represented by using the proposed method (font Calibri; size 11). [5 marks] 1. Produce a report on designing a complete experimental learning framework for the thorough analysis on whether a new student can pass the module or not (based on the sample dataset). [30 marks] Sample Dataset Coursework Attendance Pass Module Coursework 2 5 4 6 7 4 5 6 5 9 6 5 Student 1 2 Student 2 0 Student 3 6 Student 4 7 Student 5 Student 6 8 Student 7 9 Student 8 2 Student 9 Student 10 1 Student 11 10 Student 12 3 Student 13 6 Student 14 7 Student 15 2 Student 16 9 Student 17 6 Student 18 5 Student 19 6 Student 20 3 Student 21 7 Student 22 6 Student 23 8 Student 24 10 Student 25 3 *? Unknown More than 80% Less than 80% 80% 80% Less than 80% 80% More than 80% More than 80% Less than 80% Less than 80% More than 80% Less than 80% 80% 80% More than 80% More than 80% Less than 80% 80% Less than 80% 80% More than 80% More than 80% More than 80% More than 80% More than 80% Asking Questions in the class Often Seldom Never Often Often Often Never Seldom Never Often Seldom Seldom Seldom Seldom Seldom Never often Never Never Often often Seldom Often Often Never Y ? ? ? N Y Y N Y N Y 7 2 2 ? 6 7 8 9 10 2 N Y ? 7 10 6 10 4 5 ? ? ? ? ? ? Report Structure The report should have the following sections: o Description of the sample dataset. Analyse in quantitative terms the characteristics of the datasets (e.g. number and type of attributes, number of instances, class distribution, etc.). (4 marks) o Brief description of the chosen learning framework and justify why it will work. (8 marks) Details of the design. Explain all the learning process (e.g. how to prepare the training and test sets, list of components...) and how learning algorithm/algorithms can be implemented to do the analysis (e.g. what the learning algorithm is, how it works with the sample dataset,.....). The goal of this section is to describe the setup of the learning framework you do in a way that anybody that reads your description is able to replicate them. (10 marks) Performance evaluation. Describe how you are going to evaluate the performance of the learning framework. (4 marks) o Conclusions. Brief summary containing the highlights of your design. (4 marks) Report Length Provide your answer in a maximum of 2 pages (font Calibri; size 11). 2. Choose a knowledge representation method for instances in Sample Dataset with justification and show how student 1 and student 5 could be represented by using the proposed method (font Calibri; size 11). [5 marks]