You have obtained data for a sample of 50,000 survey respondents containing brief text descriptions of the nature of their job and a job code (e. g., accountant, engineer) that has been assigned by expert coders based on these text descriptions. You fit a machine learning model that uses the words in the text descriptions to explain the job code assigned by the expert coders. You use all 50,000 observations to estimate the model parameters that do the best job of fitting the job codes for those 50,000 observations, and the model seems to do a good job. When you use the model you have estimated to auto-code the following yearâs survey responses, however, it performs poorly. Required:
What might explain why your model does not perform well in explaining the following yearâs data? Briefly describe something you might you have done to avoid this problem.