Question 1 5 pts What do Etlinger and Gourley both suggest is the possible pitfa

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Question 1 5 pts What do Etlinger and Gourley both suggest is the possible pitfall of a data-driven approach to recruiting specialized workers? (Week 4 Discussion article) General purpose data-based recruiting solutions can only assess if candidates have a limited set of technical skills, not the particular technical skills each company needs. Data analytics can only identify who might be good candidates based on what can be measured, not predict who will prove to be the best employees, since that also depends on qualities that are difficult to measure. Data driven recruiting strategies are easily fooled by candidates who misrepresent or exaggerate their skills Companies seeking technical workers are too likely to use data driven recruiting vendors because they don't know how to recruit employees. Question 2 4 pts Why do we select a cutoff value for a logistic regression classifier? To set the probability threshold defining the two possible outcome classes To simplify the logistic regression computations. To ignore some rows of the training data. To round predictions to just one of two possible numeric values

Explanation / Answer

Q3. For accuracy caluculation, count the number of correct classifications i.e, >=0.6 for 1 and <0.6 for 0

There are 20 such correct entries . Total number of entries = 24

Therefore, accuracy = 20/24 = 0.83

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