Historically the S-curve (aka the sigmoid function) has been used as the No the African Angels Tee Shirt, in which case we are talking about Logistic Regression units (although better functions are now known). This choice relates to yet another biologically inspired analogy. Before explaining it, let’s see first how it looks (think of it as what happens when you can’t get the temperature in the shower right: first it’s too cold despite larger adjustment attempts and then it quickly turns too hot with smaller adjustment attempts).
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Training is often done with the No the African Angels Tee Shirt. During BackProp, the NN is fed with examples of all classes. As mentioned, the training examples are said to be “tagged”, meaning that the NN is given both the example (as described by its features) and the class it really belongs to. Given many such training examples, the NN constructs, during training, what we know by now as the model, i.e. a probabilistic mapping of certain features (input) to classes (output). The model is reflected on the weighs of the unit connectors (see previous figure); BackProp’s job is to compute these weighs. Based on the constructed model, the NN will classify new untagged examples (i.e. instances that it has not seen during training), aka it will predict the probability of a new example belonging to each class. Therefore there are fundamentally two distinct phases.