The confusion matrix shows the number of observed response variables which are inaccurately classified.
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Q9: The confusion matrix for a classification tree
Q10: The confusion matrix shows the number of
Q11: One approach to avoid overfitting a classification
Q12: To "overfit" the data is to adjust
Q13: Because different classification techniques will perform better
Q15: A regression tree is used for predicting
Q16: Classification involves identifying common traits in items
Q17: The nearest neighbors to an observation are
Q18: The best value of k to use
Q19: The confusion matrix is not a good
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