Step 1: You are required to perform a data mining task to evaluate different classification algorithms. Load thevote.arffdata set into Weka and compare the performance on this data set for three...

Step 1: You are required to perform a data mining task to evaluate different classification algorithms. Load thevote.arffdata set into Weka and compare the performance on this data set for three classification algorithms:

• Decision Tree


• Naive Bayes


• k-Nearest Neighbour

Step 2: From step 1 outputs, write a report that shows the performance of the different algorithms and comment on their accuracy using the confusion matrix and other performance metrics used in Weka. In your report consider:

• Is there a difference in performance between the algorithms?


• Which algorithm performs best?

Your report should Include the necessary screenshots, tables, graphs, etc. to make your report understandable to the reader.

The task is worth 15 marks of the overall marks available for assessment 3.

Rationale

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This assessment task will work towards assessing the following learning outcome/s:

• be able to identify and analyse business requirements for the identification of patterns and trends in data sets.


• be able to appraise the different approaches and categories of data mining problems.


• be able to compare and evaluate output patterns.


• be able to explore and critically analyse data sets and evaluate their data quality, integrity and security requirements.


• be able to compare and evaluate appropriate techniques for detecting and evaluating patterns in a given data set.


• be able to explain the importance of current and future trends likely to affect data mining and visualisation.

Marking criteria and standards

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The grade you receive for this assessment as a whole is determined by the cumulative marks gained for each question. The tasks in this assessment involve a sequence of several steps and therefore you will be marked on the correctness of your answer as well as clear and neat presentation of your diagrams,