Convergence Proof for Unsteady Classification Model with Data Fluctuations
Peng Wu · Applied Mechanics and Materials · 2014
Convergence of unsteady classification model with data fluctuations has strong application value. This paper models the mathematical problem to verify the feasibility and finite convergence of unsteady classification model with data fluctuations, and verifies the feasibility and limited convergence of the model by convex optimization KKT equivalent conditions from different perspectives. Experiments validate the three real data sets collected, and results show that the proposed model is feasible and finite convergence.