Assessment Task Task 1 (20 marks) In WEKA load the data set DIABETES.arff. Perform rule classification using the following methods • JRip • Ridor For each method produce a summary of the rules produced and comment on the accuracy of the method. Task 2 (20 marks) In WEKA load the data set supermarket.arff. Perform association rule learning using the following methods • Apriori • FPGrowth For each method produce a summary of the rules produced and comment on the accuracy of the method. Task 3 (20 marks) In WEKA load the data set breat-cancer.arff. Perform Bayesian classification using the following methods • AODE • BayesNet For each method produce a summary of the classification produced and comment on the accuracy of the method. Rationale To gain understanding of main methods for • Rules classification • Association rule learning • Rule creation using Bayesian Analysis Marking criteria Task 1 (20 marks) The specific marking criteria for this question are Question Crireria Marks JRip (10 marks) Description of JRip and describing model output 4 Cross validation summary discussion 3 Discussion of model accuracy 3 Ridor (10 marks) Description of JRip and describing model output 4 Cross validation summary discussion 3 Discussion of model accuracy 3 The generic marking criteria for this question are Question HD DI CR PS JRip (10 marks) The student has thoroughly understood the classification method, providing a detailed description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates thorough understanding of the classification method as applied to the given data set The student has understood the classification method, providing a detailed description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates detailed understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model shows basic understanding of the classification method as applied to the given data set. Ridor (10 marks) The student has thoroughly understood the classification method, providing a detailed description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates thorough understanding of the classification method as applied to the given data set The student has understood the classification method, providing a detailed description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates detailed understanding of the classification method as applied to the given data set The student has understood the classification method, providing a description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model shows basic understanding of the classification method as applied to the given data set. Task 2 (20 marks) The specific marking criteria for this question are Question Criteria Marks Apriori (10 marks) Description of Apriori and describing model output 5 Discussion of model accuracy 5 FPGrowth (10 marks) Description of FPGrowth and describing model output 5 Discussion of model accuracy 5 The generic marking criteria for this question are Question HD DI CR PS Apriori (10 marks) The student has thoroughly understood the classification method, providing a detailed description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates thorough understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a detailed description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates detailed understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model shows basic understanding of the classification method as applied to the given data set. FPGrowth (10 marks) The student has thoroughly understood the classification method, providing a detailed description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates thorough understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a detailed description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates detailed understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model shows basic understanding of the classification method as applied to the given data set. Task 3 (20 marks) The specific marking criteria for this question are Question Criteria Marks AODE (10 marks) Description of AODE and describing model output 4 Cross validation summary discussion 3 Discussion of model accuracy 3 BayesNet (10 marks) Description of BayesNet and describing model output 4 Cross validation summary discussion 3 Discussion of model accuracy 3 The generic marking criteria for this question are Question HD DI CR PS AODE (10 marks) The student has thoroughly understood the classification method, providing a detailed description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates thorough understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a detailed description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates detailed understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model shows basic understanding of the classification method as applied to the given data set. BayesNet (10 marks) The student has thoroughly understood the classification method, providing a detailed description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates thorough understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a detailed description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates detailed understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model demonstrates understanding of the classification method as applied to the given data set. The student has understood the classification method, providing a description of the method and its output on the given data set. The discussion involving the validation and accuracy of the model shows basic understanding of the classification method as applied to the given data set. Presentation • Assignments are required to be submitted in either Word format (.doc, or .docx), Open Office format (.odf), Rich Text File format (.rtf) or .pdf format. Each assignment must be submitted as a SINGLE document. • Assignments should be typed using 10 or 12 point font. APA referencing style should be used. A reference list should be included with each assessment item. • All diagrams that are required should be inserted into the document in the appropriate position. Diagrams that are submitted in addition to the assignment document will not be marked.