A logistic regressor
As we just explained, the simplest neural network is a logistic regressor. A logistic regression takes in values of any range but only outputs values between zero and one.
There is a wide range of applications where logistic regressors are suitable. One such example is to predict the likelihood of a homeowner defaulting on a mortgage.
We might take all kinds of values into account when trying to predict the likelihood of someone defaulting on their payment, such as the debtor's salary, whether they have a car, the security of their job, and so on, but the likelihood will always be a value between zero and one. Even the worst debtor ever cannot have a default likelihood above 100%, and the best cannot go below 0%.
The following ...
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