The Deception of Supervised Learning
Do models or offline datasets ever really tell us what to do? Most application of supervised learning is predicated on this deception. Imagine you're a doctor tasked with choosing a cancer therapy. You could think hard about the problem and come up with some rules. But these rules would be overly simplistic, not personalized to the patient or customer.
Sep-14-2016, 05:05:48 GMT
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- North America > United States > California (0.15)
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- Research Report (0.50)
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- Health & Medicine > Therapeutic Area > Oncology (0.35)
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