What foundational principle highlights that flawed training data leads to flawed predictions in predictive modeling?
Answer
Garbage in, garbage out
The text explicitly mentions the core principle 'garbage in, garbage out,' meaning if the historical data used to train a predictive model is incomplete or inaccurate, the resulting predictions will inherently be flawed from the start.
Related Questions
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