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Machine decisions result from learning from data.
Statistics is the art of learning from data.
For the second type of problems, standard automation is not enough – they require learning from data.
Learning From Data: General Issues and Special Applications of Radial Basis Function Networks.
Statistics is the overarching discipline concerned with everything related to learning from data.
But machine learning is not so good at inference, learning from data about underlying science and market mechanisms.
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They are fundamentally limited because they learn from data.
What can policy students learn from data analysis?
This is where big data and machine learning (systems that can learn from data) can level the playing field.
Once the BBN is learned from data, it can be further used for prediction.
Ensemble methods provide a way to learn from data more accurately.
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