Support Vector Machines — Lecture series — Sequential Minimal Optimization Part 3

  1. Iterate through all of the examples in the dataset to find the examples whose Lagrange multipliers are not bound, since those examples are more likely to violate the KKT conditions. Lagrange multipliers that are not bound are those that are neither 0 nor C.
  2. Go through the subset of examples obtained from the first pass over the dataset in the first step to identify examples that actually do not satisfy the KKT conditions.
  3. The examples generated from step 2 are the examples whose Lagrange multipliers should be chosen and optimized.
  4. After the Lagrange multipliers of the examples in step 3 have been optimized, go through all of the examples in the dataset again to ensure that none of the examples violate the KKT conditions.

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