Why do we split the dataset into training and test data

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Reference no: EM131871934

Assignment

1. Identify the dependent variable and independent variables in the Credit Approval data set.

2. provide a one-paragraph masters-level response describing what you anticipate that the ctree (conditional inference tree) method will accomplish for the Credit Approval data? Be specific about the behavior and structure of tree-based models.

3. Why do we split the dataset into training and test data? Provide a oneparagraph, masters-level response in your own words.

4. interpret the structure of the model including the splitting and leaf nodes in your discussion. Provide a one-paragraph, masters-level response.

5. Based on the results of your ctree model, which independent variables could be significant predictors of the dependent variable? Justify why you made this conclusion by supporting your answer with specific references to the ctree model itself. Provide a one-paragraph, masters-level response.

6. What differences did you observe between the Apriori association rules method and the Conditional Inference ctree method? Compar and contrast at least two characteristics from each method. Provide a one-paragraph, masters-level response.

7. Do missing values affect the results of the ctree model? Provide a oneparagraph, masters-level response.

Attachment:- newcredit.rar

Reference no: EM131871934

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