enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Support vector machine - Wikipedia

    en.wikipedia.org/wiki/Support_vector_machine

    The original maximum-margin hyperplane algorithm proposed by Vapnik in 1963 constructed a linear classifier. However, in 1992, Bernhard Boser, Isabelle Guyon and Vladimir Vapnik suggested a way to create nonlinear classifiers by applying the kernel trick (originally proposed by Aizerman et al. [20]) to maximum-margin hyperplanes. [7]

  3. Hinge loss - Wikipedia

    en.wikipedia.org/wiki/Hinge_loss

    The plot shows that the Hinge loss penalizes predictions y < 1, corresponding to the notion of a margin in a support vector machine. In machine learning, the hinge loss is a loss function used for training classifiers. The hinge loss is used for "maximum-margin" classification, most notably for support vector machines (SVMs). [1]

  4. Hyperplane separation theorem - Wikipedia

    en.wikipedia.org/wiki/Hyperplane_separation_theorem

    A related result is the supporting hyperplane theorem. In the context of support-vector machines, the optimally separating hyperplane or maximum-margin hyperplane is a hyperplane which separates two convex hulls of points and is equidistant from the two. [1] [2] [3]

  5. Linear separability - Wikipedia

    en.wikipedia.org/wiki/Linear_separability

    So we choose the hyperplane so that the distance from it to the nearest data point on each side is maximized. If such a hyperplane exists, it is known as the maximum-margin hyperplane and the linear classifier it defines is known as a maximum margin classifier.

  6. Hyperplane - Wikipedia

    en.wikipedia.org/wiki/Hyperplane

    In geometry, a hyperplane of an n-dimensional space V is a subspace of dimension n − 1, or equivalently, of codimension 1 in V.The space V may be a Euclidean space or more generally an affine space, or a vector space or a projective space, and the notion of hyperplane varies correspondingly since the definition of subspace differs in these settings; in all cases however, any hyperplane can ...

  7. Musk and Ramaswamy won't be paid to lead new Department of ...

    www.aol.com/musk-ramaswamy-wont-paid-lead...

    Elon Musk shared on X that nor he or Vivek Ramaswamy will be paid to co-lead the newly-created Department of Government Efficiency.

  8. Margin (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Margin_(machine_learning)

    Hence, one should choose the hyperplane such that the distance from it to the nearest data point on each side is maximized. If such a hyperplane exists, it is known as the maximum-margin hyperplane, and the linear classifier it defines is known as a maximum margin classifier (or, equivalently, the perceptron of optimal stability). [citation needed

  9. GM CFO reveals banned word inside company, saying it's a new GM

    www.aol.com/gm-cfo-reveals-banned-word-040022447...

    GM's CFO told investors the company has changed its business strategy to withstand market volatility and a new presidential administration.