Should Validation Differ with Machine Learning? No!
Machine learning is nothing more than a small space of statistics. We are building models on the same data sets to model the same problems. Why would the process change for this? Why would you blindly use a method and do minimal or no testing? I ask these because the machine learning and data science community has been trying to convince people that ML models are a magic pill to fix everything. It doesn't change much besides a new approach with the same data and business problem restrictions.
For validations make sure to review the data sampling and cleaning, conceptual soundness, model performance, and model governance.
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1 окт 2024