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brownzackery71
brownzackery71
21.10.2019 • 
Mathematics

When the goal is to accurately classify the top tier of a new sample rather than accurately classify the entire sample, these charts are used to assess performance? 1 bar,2 lift, 3 decline charts, 4 none

this means that the observation belongs to one class but the model classifies it as member of a different class? 1 average error, 2 misclassification error, 3 prediction error, 4 all

a very simple rule for classifying a record into one of m classes, ignoring all predictor information that we may have, is to classify the record as a member of the majority class? 1 classification matrix rule, 2 class separation rule, 3 naive rule, 4 none

a popular method of plotting the pairs (sensitivity, 1-specificity) as the cutoff value increases from 0 and 1. 1 roc curve, 2 scatter plot, 3 lift charts, 4decile charts

when classifying data with very low response rates, practitioners typically. 1 train models on data that are 50% responder, 2 train models on data that are 50% nonresponder, 3 validate the models with an unweighted sample from the original data, 4 all the above

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