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As in the classification algorithm proposed by Joachims ,
which was based on a idea from Osuna et al ,
our regression algorithm is subdivided
into the following four steps, which are explained afterward in the
- Select q variables
as the new working set, called
- Fix the other variables
to their current values and
solve the problem (3) with respect to
- Search for variables whose values have been at 0 or C for a long
time and that will probably
not change anymore. This optional step is the shrinking phase,
as these variables are removed from the problem.
- Test whether the optimization is finished; if not,
return to the first step.
Many other decomposition algorithms for regression have been published
recently, and a comparison is given later in section 2.6.
Journal of Machine Learning Research