ITC516 Data Mining & Visualisation for B.Intelligence Weka Data Mining

Charles Sturt University


ITC516 - Data Mining and Visualisation for Business Intelligence Weka Data Mining

Assessment No: 3

ITC516|Data Mining and Visualisation for Business Intelligence

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ITC516 - Data Mining and Visualisation for Business Intelligence Weka Data Mining

Weka Data Mining


Task

Task: Weka Data Mining Practical and Report [15 marks]

There are two steps to complete in this task:

Step 1

You are required to perform a data mining task to evaluate different classification algorithms. Load the soybean.arff data set into Weka and compare the performance on this data set for the following classification algorithms:

  • Naive Bayes
  • HoeffdingTree
  • SVM
  • J48
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.

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