ITC516 - Data Mining and Visualisation for Business Intelligence Weka

Charles Sturt University


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

Assessment No: 2

ITC516|Data Mining and Visualisation for Business Intelligence

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

Weka and Written Exercise


Task

For this assessment, you are required to use Weka 3.8.3 (or a later version available at https://www.cs.waikato.ac.nz/ml/weka/downloading.html ), you will use this throughout the duration of this subject.

Task 1: Weka data exploration [3 marks]

Load the contact-lenses.arff dataset in Weka and answer the following questions.

  • What are the domain values for the attributes age and astigmatism? [1 mark]
  • List the class domain values of the data set? [1 mark ]
  • Load the iris.arff dataset and open it in the editor by clicking the ‘Edit’ button from the row of buttons at the top of the ‘Preprocess’ panel in Weka Interface and answer the following questions. How many numeric and how many nominal attributes does this dataset have? Also write the statistical information of the numerical attributes. [1 mark]

Task 2: Working with a new data file in Weka [4 marks]

Consider the Marks data set (Marks.txt is available at the student resources of your subject interact2 site) which represents the assessment results of 40 students in a subject consisting of four assignments and final exam.

  • Create an ARFF file by using a text editor for this dataset and open the ARFF file in Weka. [1 mark]
  • Apply the unsupervised Discretize filter to the attribute Assignment-4 in the marks dataset. Put a screenshot of the filter output in your assignment and make some remarks on the data. [1 mark]
  • Practice filling in the missing values for all columns in the Viewer window in Weka both manually and by using filters. Put a screenshot of the filter outputs in your assignment and make comments on what values are suggested by WEKA for the missing values? [2 marks]

Task 3: Visualization and Analysis [4 marks]

You will also do some tasks with the Weka software for data visualization and analysis. This task will build the practical and technical skills that will enable you to compare and evaluate output patterns for visualization.

Load the contact-lenses.arff dataset in Weka and answer the following questions.

  • What is the range of possible values for each of the 4 attributes that can be observed in the dataset? [2 marks]
  • Present a scatter plot visualization of this dataset and find which two classes have more overlapping tendency and which one is likely to be a separate class as observed in the attribute-pair based plotting. Alternatively, you may use the 3D visualization feature provided in Weka to find the followings based on different combinations of any three featuring attributes out of four attributes in the dataset: (i) which two classes have more overlapping tendency, and (ii) which one is likely to be a separate class. [2 marks]

Task 4: Written Exercise [4 marks]

Topic: Security, Privacy and Ethics in Data Mining.

In this task, you are required to read the journal articles provided below and write a short discussion paper based on the topic of security, privacy and ethics in data mining. You must:

  • identify the major security, privacy and ethical implications in data mining;
  • evaluate how significant these implications are for the business sector; and
  • support your response with appropriate examples and references.

The recommended word length for this task is 700 to 1000 words.

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