Q: 12
[Modeling]
A finance company needs to forecast the price of a commodity. The company has compiled a dataset
of historical daily prices. A data scientist must train various forecasting models on 80% of the dataset
and must validate the efficacy of those models on the remaining 20% of the dataset.
What should the data scientist split the dataset into a training dataset and a validation dataset to
compare model performance?
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