You Ask, I Answer: Hypothesis Formation Without Data Snooping in Marketing Data Science?

Описание: Jessica asks, "How would you differentiate hypothesis formation and searching for relevant variables WITHOUT "data snooping"?"

Data snooping, or more commonly known as curve fitting or data dredging, is when you build a hypothesis to fit the data. The way to avoid this is by using evidence not included in the dataset you used to build your hypothesis, which is cross-validation. It's like A/B testing. Most good machine learning tools do this as a best practice, and we should replicate it - they will split a dataset into a training set, a test set, and a validation set. You'll do this best by starting with a sample of your dataset and then adding new data once you've done your initial exploratory data analysis.

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