Kernels and Ensembles : Perspectives on Statistical Learning

  title={Kernels and Ensembles : Perspectives on Statistical Learning},
  author={Mu Zhu},
Since their emergence in the 1990s, the support vector machine and the AdaBoost algorithm have spawned a wave of research in statistical machine learning. Much of this new research falls into one of two broad categories: kernel methods and ensemble methods. In this expository article, I discuss the main ideas behind these two types of methods, namely how to transform linear algorithms into nonlinear ones by using kernel functions, and how to make predictions with an ensemble or a collection of… CONTINUE READING
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