Assignment Problem:
Rapid growth in size and number of databases in recent years surpasses human ability to carry out effective and efficient data analysis. There is a need to build computerized mechanisms for recognizing and characterizing the data, in particular, using known facts and trends as well as to discover new and interesting facts.
In this Assignment, you are required to identify and characterize a data set in the field of your choice using Weka datamining package. You can use the following links to find a preferred dataset. You should get approval from the lecturer before commencing your assignment.
Your report should cover the following:
Introduction: Introduction should include the background to the topic. The purpose of the assignment and what type of benefit you might hope to get from data mining.
Data Description: Provide description to the data set. Categorize each variable as nominal or numeric, continuous or discrete and whether or not it is of use in building the solution. Explain your decisions.
Data Pre-processing: Document the data pre-processing/transforming tasks you applied for any feature/variable. Show histograms of the data before and after any pre-processing that you carried out using screen shots.
Data Modelling: Apply any four classification algorithm to the dataset. Give a brief technical description of the techniques and the way the models are represented. Describe the different techniques you used and the results that you got. All the models will be learned and tested by splitting the dataset in a training and a test dataset, each of which consisting in 70% and 30% of instances, respectively. For each built model, include in you report a screenshot with the algorithm name and the parameter values chosen for its application, and a screenshot with the confusion matrix and the measures of performance of the model (in particular the accuracy). Calculate for each model the precision, sensitivity, specificity and the lift. Choose the best model and justify your answer.
Conclusion: Conclusion should include whether you were able to achieve the purpose of the report. How your approach can be improved in the future?
Data: Links to some data sources you can use for your assignment. The list is not exhaustive as you can suggest any dataset of your choice.
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Attachment:- Weka datamining package.rar