论文信息 - SMO algorithm for least squares SVM

SMO algorithm for least squares SVM

This paper extends the well-known SMO (Sequential Minimal Optimization) algorithm of Support Vector Machines (SVMs) to Least Squares SVM formulation. The algorithm is asymptotically convergent. It is also extremely easy to implement. Computational experiments show that the algorithm is fast and scales efficiently (quadratically) as a function of the number of examples.

S. Keerthi | S. Shevade

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