Consider the following result from a classification problem and a model built for it. Predicted Yes...
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Consider the following result from a classification problem and a model built for it. Predicted Yes Predicted No Total Actual Yes 223 43 266 Actual No 87 453 540 Total 310 496 806 1. What is the value of the following metrics given the result table above? Accuracy Precision Recall F1-score 2. Sometimes, the cost of errors is not constant. For example, if we were predicting whether a patient has cancer, a false negative could be considered much worse than a false positive. If that were the case, which of the above statistics would you want to optimize? Briefly explain why. Consider the following result from a classification problem and a model built for it. Predicted Yes Predicted No Total Actual Yes 223 43 266 Actual No 87 453 540 Total 310 496 806 1. What is the value of the following metrics given the result table above? Accuracy Precision Recall F1-score 2. Sometimes, the cost of errors is not constant. For example, if we were predicting whether a patient has cancer, a false negative could be considered much worse than a false positive. If that were the case, which of the above statistics would you want to optimize? Briefly explain why.
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The image you sent contains a confusion matrix for a classification problem A confusion matrix shows the number of correct and incorrect predictions made by a classification model In this case the mod... View the full answer
Related Book For
Income Tax Fundamentals 2013
ISBN: 9781285586618
31st Edition
Authors: Gerald E. Whittenburg, Martha Altus Buller, Steven L Gill
Posted Date:
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