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Your data science intern Rox was asked to create a decision tree classifier with 12 input variables. The tree used 7 of the 12 variables, and was 5 levels deep. Few nodes of the tree contain 3 data points. The area under the curve (AUC) is 0.86. As Rox's mentor, what is your interpretation?
A. The AUC is high, and the small nodes are all very pure- the model looks accurate.
B. The tree might be overfitting- try fitting shallower trees and using an ensemble method.
C. The AUC is high, so overall the model is accurate. It might not be well-calibrated, because the small nodes will give poor estimates of probability.
D. The tree did not split on all the input variables. We need a larger data set to get a more accurate model.
Customized by subject matter experts to cater to job roles for all experience levels (fresh grads to 8-10 years) within your organization.
Adaface assessments have an average test taking rate of 86% as compared to an industry standard of 50%.
Adaface assessments have relevant questions that test for on-the-job skills. We do not expect candidates to solve puzzles/ trick questions.
We evaluated several of their competitors and found Adaface to be the most compelling. Great default library of questions that are designed to test for fit rather than memorization of algorithms.
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