Not-supervised training
The training not-supervised is a machine method of Learning. This method is distinguished from the Apprentissage supervised by the fact that there is no exit a priori . In the not-supervised training there is in entry a whole of collected data. Then the program treats these data like random variable and built a model of densities united for this unit of data.
The not-supervised training can also be used in conjunction with a Inférence bayésienne to produce conditional probabilities for each random variable being given the different ones.
Another form of not-supervised training is the Partitionnement of data which is not always probabilist.
See too
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