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Machine Learning: Fundamentals and Applications Quiz 2 Linear Classification 1

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With the given confusion matrix, what is the misclassification rate? Actual Label Y: 1 Actual Label Y: 0 Predicted Model h: 1 10 1 Predicted Model h: 0 5 6

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The question asks for the misclassification rate given the confusion matrix. First, I restate the matrix in a clear way: - Predicted h = 1, Actual Y = 1: 10 - Predicted h = 1, Actual Y = 0: 1 - Predicted......Login to view full explanation

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Consider the targeted marketing campaign case of selling products through promotional catalogs. The following tables show the confusion matrices of the classification tree model and the logit regression model, which classifies customers into 'likely to respond' (positive) and 'not likely to respond' (negative). Confusion Matrix of the Classification Tree Model: p (actual) n (actual) p (predicted) 10 4 n (predicted) 3 15   Confusion Matrix of the Logit Regression Model: p (actual) n (actual) p (predicted) 13 5 n (predicted) 2 12 Which model is more accurate (higher accuracy rate) based on the information given in these confusion matrices?

Which factor(s) will increase when the prediction agrees with the gold standard.

The sum true positives + false negatives equals:

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