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  2. Linear separability - Wikipedia

    en.wikipedia.org/wiki/Linear_separability

    H 1 does not separate the sets. H 2 does, but only with a small margin. H 3 separates them with the maximum margin. Classifying data is a common task in machine learning. Suppose some data points, each belonging to one of two sets, are given and we wish to create a model that will decide which set a new data point will be in.

  3. Kirchberger's theorem - Wikipedia

    en.wikipedia.org/wiki/Kirchberger's_theorem

    Kirchberger's theorem is a theorem in discrete geometry, on linear separability.The two-dimensional version of the theorem states that, if a finite set of red and blue points in the Euclidean plane has the property that, for every four points, there exists a line separating the red and blue points within those four, then there exists a single line separating all the red points from all the ...

  4. Perceptron - Wikipedia

    en.wikipedia.org/wiki/Perceptron

    In case the training set D is not linearly separable, i.e. if the positive examples cannot be separated from the negative examples by a hyperplane, then the algorithm would not converge since there is no solution. Hence, if linear separability of the training set is not known a priori, one of the training variants below should be used.

  5. Linear subspace - Wikipedia

    en.wikipedia.org/wiki/Linear_subspace

    If V is a vector space over a field K, a subset W of V is a linear subspace of V if it is a vector space over K for the operations of V.Equivalently, a linear subspace of V is a nonempty subset W such that, whenever w 1, w 2 are elements of W and α, β are elements of K, it follows that αw 1 + βw 2 is in W.

  6. Separability - Wikipedia

    en.wikipedia.org/wiki/Separability

    Separable filter, a product of two or more simple filters in image processing; Separable ordinary differential equation, a class of equations that can be separated into a pair of integrals; Separable partial differential equation, a class of equations that can be broken down into differential equations in fewer independent variables

  7. Cover's theorem - Wikipedia

    en.wikipedia.org/wiki/Cover's_Theorem

    The left image shows 100 points in the two dimensional real space, labelled according to whether they are inside or outside the circular area. These labelled points are not linearly separable, but lifting them to the three dimensional space with the kernel trick, the points becomes linearly separable. Note that in this case and in many other ...

  8. Indo-U.K. Sports Drama ‘A Game of Two Halves ... - AOL

    www.aol.com/entertainment/indo-u-k-sports-drama...

    Indo-British sports drama “A Game of Two Halves,” which champions equal opportunities for underprivileged children through soccer, has unveiled its first trailer. The coming-of-age film, set ...

  9. Separable extension - Wikipedia

    en.wikipedia.org/wiki/Separable_extension

    For instance, the polynomial g(X) = X 21 has precisely deg g = 2 roots in the complex plane; namely 1 and −1, and hence does have distinct roots. On the other hand, the polynomial h ( X ) = ( X − 2) 2 , which is the square of a non-constant polynomial does not have distinct roots, as its degree is two, and 2 is its only root.