Talk:Support vector machine/Archives/2019
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How is that relevant?
How is the section
When data is unlabelled, supervised learning is not possible, and an unsupervised learning approach is required, which attempts to find natural clustering of the data to groups, and then map new data to these formed groups. The support-vector clustering[2] algorithm, created by Hava Siegelmann and Vladimir Vapnik, applies the statistics of support vectors, developed in the support vector machines algorithm, to categorize unlabeled data, and is one of the most widely used clustering algorithms in industrial applications
relevant for this article? Should we delete it? --Raffamaiden (talk) 12:58, 26 May 2019 (UTC)
- See the bottom of this talk page (and that is where you should add new entries, btw.). But I do consider Vladimir Vapnik to be an authority on SVMs... HelpUsStopSpam (talk) 19:27, 26 May 2019 (UTC)