I have identified five primary reasons why analytical models fail:
- Poor Organizational Support
- Missing Causes
- Model Overfit
- Data Problems
- False Beliefs
In this post, we will consider how and why Missing causes in the data for training a model may result in incorrect inferences or failures.
This post first appeared on Elder Research Data Science & Machine Learning Blog, please read the originial post: here