Consistent Model Combination for SVR via Regularization Path ⋆
نویسندگان
چکیده
It is well-known that model combination can improve prediction performance of regression model. We investigate the model combination of Support Vector Regression (SVR) with regularization path in this paper. We first define Lε-risk of SVR, and prove that SVR regularization path leads to at least one Lε-risk consistent fitted model. Then we establish the Lε-risk consistency for convex combination of SVR base fitted model, which gives the mathematical justification for model combination of SVR on regularization path. With the inherent piecewise linearity of SVR regularization path, we propose an effective method for Beyesian model combination. Theoretical analysis and experimental results suggest the feasibility of the proposed method.
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