Conditional probability for classification In Book "Machine Learning: A probabilistic Perspective" Page 30, it tries to give a generative classifiers solution using conditional probability as
$$p(y=c|x,\theta)=\frac{p(y=c|\theta)p(x|y=c,\theta)}{\sum_{c'}p(y=c'|\theta)p(x|y=c',\theta)}$$
I understand the numerator but I don't understand the denominator. How did they come to that?

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*When Andrea needs a taxi, she rings one of three taxi companies, A, B or C. 50% of her calls are to taxi company A, 30% to B and 20% to C. A taxi from company A arrives late 4% of the time, a taxi from company B arrives late 6%of the time and a taxi from company C arrives late 17% of the time.

