Linear kernel combination using boosting
نویسندگان
چکیده
In this paper, we propose a novel algorithm to design multiclass kernels based on an iterative combination of weak kernels in a schema inspired from the boosting framework. Our solution has a complexity linear with the training set size. We evaluate our method for classification on a toy example by integrating our multi-class kernel into a kNN classifier and comparing our results with a reference iterative kernel design method. We also evaluate our method for image categorization by considering a classic image database and comparing our boosted linear kernel combination with the direct linear combination of all features in a linear SVM.
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