Based on dataset run Apriori algorithm with different support and confidence values. Discuss the generated rules.
1 Marks Learning Outcome(s):1 Explain different data mining tasks, problems and the algorithms most appropriate for addressing them Question One
Select one of the datasets from UCI Machine Learning Repositories
(http://archive.ics.uci.edu/ml/) OR ( https://www.kaggle.com/datasets )
OR use your own dataset if available.
1 Marks Learning Outcome(s): 2 Apply and evaluate data mining algorithms with respect to problems they are specifically designed for. Question Two
The dataset may follow the following requirements (Data description)
- Number of instances: between 300-500
- Number of attributes: between 10 to 15
0.5 Marks Learning Outcome(s):1 Explain different data mining tasks, problems and the algorithms most appropriate for addressing them. Question Three
Prepare a CSV OR ARFF format data file of the data.
0.5 Marks Learning Outcome(s):1 Explain different data mining tasks, problems and the algorithms most appropriate for addressing them. Question Four
Load the dataset in Weka or if you prefer to use any python tools such as Google Collaborate Lab https://research.google.com/colaboratory/
2 Marks Learning Outcome(s): 2 Apply and evaluate data mining algorithms with respect to problems they are specifically designed for. Question Five
Do a basic preprocessing to the dataset such data cleaning / Data reduction /Normalization (if exist or required) etc.
Learning Outcome(s): 2 Apply and evaluate data mining algorithms with respect to problems they are specifically designed for. 2 Marks Question six
Based on dataset run Apriori algorithm with different support and confidence values. Discuss the generated rules.
Learning Outcome(s): 2 Apply and evaluate data mining algorithms with respect to problems they are specifically designed for. 1 Mark Question seven
Based on your dataset selection, apply SVM data mining algorithm.
Provide the result and accuracies of the algorithms and discuss it with supporting screenshots.
Learning Outcome(s): 2 Apply and evaluate data mining algorithms with respect to problems they are specifically designed for. 1 Mark Question eight
Based on your selection dataset, Apply the Decision tree data mining algorithm with different parameter setting and record the accuracies.
Learning Outcome(s): 2 Apply and evaluate data mining algorithms with respect to problems they are specifically designed for. 1 Mark Question nine
Apply the K-mean algorithm on the dataset (for k=4) and study the clusters formed.
