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  2. Linear separability - Wikipedia

    en.wikipedia.org/wiki/Linear_separability

    The existence of a line separating the two types of points means that the data is linearly separable In Euclidean geometry , linear separability is a property of two sets of points . This is most easily visualized in two dimensions (the Euclidean plane ) by thinking of one set of points as being colored blue and the other set of points as being ...

  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. Multi-surface method - Wikipedia

    en.wikipedia.org/wiki/Multi-surface_method

    Given two finite disjoint point sets ,, find a discriminant, : such that () >, (). If the intersection of convex hulls of the two sets is the empty set, then it is possible to use a single linear program to obtain a linear discriminant of the form, f ( x ) = c x + γ {\displaystyle f(x)=cx+\gamma } .

  5. 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 ...

  6. Separability - Wikipedia

    en.wikipedia.org/wiki/Separability

    Linear separability, a geometric property of a pair of sets of points in Euclidean geometry; Recursively inseparable sets, in computability theory, pairs of sets of natural numbers that cannot be "separated" with a recursive set

  7. Linear discriminant analysis - Wikipedia

    en.wikipedia.org/wiki/Linear_discriminant_analysis

    Linear classification in this non-linear space is then equivalent to non-linear classification in the original space. The most commonly used example of this is the kernel Fisher discriminant . LDA can be generalized to multiple discriminant analysis , where c becomes a categorical variable with N possible states, instead of only two.

  8. Separable space - Wikipedia

    en.wikipedia.org/wiki/Separable_space

    The "trouble" with the trivial topology is its poor separation properties: its Kolmogorov quotient is the one-point space. A first-countable , separable Hausdorff space (in particular, a separable metric space) has at most the continuum cardinality c {\displaystyle {\mathfrak {c}}} .

  9. 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.