Editing Transduction (machine learning) (section)

===Partitioning transduction===

Partitioning transduction can be thought of as top-down transduction. It is a semi-supervised extension of partition-based clustering. It is typically performed as follows:

 Consider the set of all points to be one large partition.
 While any partition P contains two points with conflicting labels:
   Partition P into smaller partitions.
 For each partition P:
   Assign the same label to all of the points in P.

Of course, any reasonable partitioning technique could be used with this algorithm. [[Max flow min cut]] partitioning schemes are very popular for this purpose.