1-    Explain the confusion matrix in classification methods and explain how you interpret the its number in an example such as which containers need to be selected at ports for a full inspection (for custom check)?

2-    Give two practical examples on applications of classification methods in your discipline. Provide detail explanations. You need to explain why you think classification can be used in those cases, you do not need to provide data or solve them.

3-    Give two examples related to your discipline that you need to apply over sampling partitioning before building the model. You need to provide detail explanations

4-    Assume one of the explanatory variable (named X1) in your logistic regression is a categorical variable with the following levels: low, average and high, and another explanatory variable (named X2) is also categorical with the following levels: Sydney and Melbourne. Explain how you will use them in developing your logistic regression model. How many coefficients you will have in your final model?

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