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Use the k-NN method for k=1,3,5, and 7 to classify each of the 15 points in the test set by using the training set. Make
- Use the k-NN method for k=1,3,5, and 7 to classify each of the 15 points in the test set by using the training set.
- Make a table that shows the classification for each point in the test set and for each k.
- Highlight the errors in red. Compute the error rate for each k.
- Based on your answers in part b), what value of k should you use to classify new data?
- Use the CART method to classify the flowers. Perform two splits. If there are equally good splits available, you may choose which to use.
- What variable was chosen for the first split and where was it split?
- What was the GINI for each group after the first split?
- What variables were chosen for the second split and where were they split?
- What was the GINI for each group after the second split?
- What was the total GINI after two splits?
- Draw the CART.
- Apply the model to the test set. What was the error rate on the test set?
- Use logistic regression to classify the flowers. Using Iris-setosa as the base level, set up the spreadsheet to calculate the probabilities using the model based on the following equations:
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