Microsoft Data Scientist Mock Interview
Master 30 Microsoft Data Scientist interview questions covering machine learning, Azure, and statistical modeling.
Question 28 of 30
How do you deal with an unbalanced binary classification when analyzing a data set?
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William Swansen has worked in the employment assistance realm since 2007. He is an author, job search strategist, and career advisor who helps individuals worldwide and in various professions to find their ideal careers.
This is yet another operational question asking you about how you react to a specific situation during a data analysis exercise at Microsoft. You should be able to answer this question easily as an experienced data scientist. Your answer should address the use of metrics and how they impact the analysis. Knowing this and explaining it to the Microsoft interviewer will reinforce your qualifications for a data scientist's position.
William Swansen has worked in the employment assistance realm since 2007. He is an author, job search strategist, and career advisor who helps individuals worldwide and in various professions to find their ideal careers.
"The easiest way to address an unbalanced binary classification is to review the metrics you are using in your model. Even though some metrics may be accurate, they may skew the results. Another way you can neutralize this issue is to increase the impact on the analysis for incorrectly classified and any minority class data. This results in a superior model, which produces more accurate results. Another solution is to oversample some of the minority class data or under-sample some of the majority class data, which will balance the binary classification."
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