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Suppose we have a binary classification problem. 99.8% of individuals in our sample = 0, 0.2% = 1. We downsample: we randomly sample say 1% of the individuals which =0, but keep all which =1. We fit our model to this new smaller sample, and now we have a model which produces probabilities that an individual = 1. How do we adjust our output probabilities to use this model on the population as a whole?
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Data Analyst

Interviewed at Upstart

3.9★
Dec 20, 2019

Suppose we have a binary classification problem. 99.8% of individuals in our sample = 0, 0.2% = 1. We downsample: we randomly sample say 1% of the individuals which =0, but keep all which =1. We fit our model to this new smaller sample, and now we have a model which produces probabilities that an individual = 1. How do we adjust our output probabilities to use this model on the population as a whole?

There were a couple of questions but these are the ones that I remember: 1. Tell me about yourself 2. Why apply for this position? 3. What are your strengths & weaknesses? 4. Present one of your projects 5. What do you expect from the company?
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People Data Analyst Intern

Interviewed at Fazz

3.7★
Sep 23, 2022

There were a couple of questions but these are the ones that I remember: 1. Tell me about yourself 2. Why apply for this position? 3. What are your strengths & weaknesses? 4. Present one of your projects 5. What do you expect from the company?

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