Support vectors in kernel based SVM












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What do the support vectors mean in kernel based svm? are they the vectors that are of distance 1 from the hyperplane that linearly separates the data in the higher dimensional space?
Thank you in advance










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    $begingroup$


    What do the support vectors mean in kernel based svm? are they the vectors that are of distance 1 from the hyperplane that linearly separates the data in the higher dimensional space?
    Thank you in advance










    share|cite|improve this question









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      $begingroup$


      What do the support vectors mean in kernel based svm? are they the vectors that are of distance 1 from the hyperplane that linearly separates the data in the higher dimensional space?
      Thank you in advance










      share|cite|improve this question









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      What do the support vectors mean in kernel based svm? are they the vectors that are of distance 1 from the hyperplane that linearly separates the data in the higher dimensional space?
      Thank you in advance







      statistics machine-learning






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      asked Dec 28 '18 at 13:15









      yjntyjnt

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          As in the linear case, they are vectors on the boundary. Below I annotated one example of the iris dataset, classified with a Radial Basis Function (RBF) kernel



          enter image description here






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            $begingroup$

            As in the linear case, they are vectors on the boundary. Below I annotated one example of the iris dataset, classified with a Radial Basis Function (RBF) kernel



            enter image description here






            share|cite|improve this answer









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              0












              $begingroup$

              As in the linear case, they are vectors on the boundary. Below I annotated one example of the iris dataset, classified with a Radial Basis Function (RBF) kernel



              enter image description here






              share|cite|improve this answer









              $endgroup$
















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                $begingroup$

                As in the linear case, they are vectors on the boundary. Below I annotated one example of the iris dataset, classified with a Radial Basis Function (RBF) kernel



                enter image description here






                share|cite|improve this answer









                $endgroup$



                As in the linear case, they are vectors on the boundary. Below I annotated one example of the iris dataset, classified with a Radial Basis Function (RBF) kernel



                enter image description here







                share|cite|improve this answer












                share|cite|improve this answer



                share|cite|improve this answer










                answered Dec 28 '18 at 14:58









                caveraccaverac

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