supervised learning

[Alain Grumbach]

    Often I feel troubled while readind phrases : "supervised learning"
or "unsupervised learning". What does it actually mean ?

    Usually, it refers to the fact that, for learning purpose, network
outputs are given by the "teacher". 

    But learning is a FUNCTION from EXAMPLE DATAS to WEIGHTS. The
informations needed for example datas may include network inputs, or
inputs and associated outputs. These outputs are input datas for the
learning phase. 

    Within this point of view, what would be a "unsupervised learning" ?
I should put forward the idea that unsupervised learning takes place when
example datas are not given by any teacher, i.e. when the system chooses
(may be randomly) its examples within the example space. In human learning,
there are many cases : games, common skills (driving a bicycle) ...
In symbolic learning domain, for instance, the LEX system (Mitchell) 
designs itself the examples it will process. In neural networks, such an
unsupervised learning is rare. Why ?

    Lastly, if we keep this idea, how could we name the kind of learning
which was concerned by phrase "supervised learning" ? I should put
forward the expression: "week(ly) supervised learning".

Summary : this is a proposition for a more precise phrasing :
- unsupervised learning : without any teacher information
- week(ly) supervised learning : the teacher gives input vectors only
- (fully) supervised learning : the teacher gives input and output vectors.

What is your feeling about this ?

grumbach @ ulysse.enst.fr

(Alain GRUMBACH
ENST Dept INF
46 rue Barrault
75634  PARIS Cedex 13
FRANCE)