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Elements of Causal Inference
Angol
140 b
30 nap a termék visszaküldésére
Ezt is ajánljuk
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Kemény kötésű
30.02
€
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Puha kötésű
8.68
€
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Puha kötésű
20.01
€
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Puha kötésű
11.01
€
After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem.
Információ a könyvről
Angol
