The Back-propagation algorithm

The back-prop algorithm for supervised learning from exemplars is:


Repeat:
  1. Send in inputs Ii for this exemplar.
  2. Calculate outputs yk
  3. Get given correct outputs Ok
  4. Measure E.

  5. wjk weights:
    1. Calculate all the   =   yk ( 1 - yk ) ( yk - Ok )
    2. Calculate all the   =     yj
    3. For all j,k:

  6. wij weights:
    1. Calculate all the   =   yj ( 1 - yj )   Σ k ( wjk )
    2. Calculate all the   =   Ii
    3. For all i,j:

  7. Repeat (next exemplar).


See sample code.