Training set

In artificial intelligence, a training set consists of an input vector and an answer vector, and is used together with a supervised learning method to train a knowledge database (e.g. a neural net or a naive bayes classifier) used by an AI machine.

In general, the intelligent system consists of a function taking one or more arguments and results in an output vector, and the learning method's task is to run the system once with the input vector as the arguments, calculating the output vector, comparing it with the answer vector and then changing somewhat in order to get an output vector more like the answer vector next time the system is simulated.