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minimum hyperplane

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  • Support vector machine — Support vector machines (SVMs) are a set of related supervised learning methods used for classification and regression. Viewing input data as two sets of vectors in an n dimensional space, an SVM will construct a separating hyperplane in that… …   Wikipedia

  • Supervised learning — is a machine learning technique for learning a function from training data. The training data consist of pairs of input objects (typically vectors), and desired outputs. The output of the functioncan be a continuous value (called regression), or… …   Wikipedia

  • K-set (geometry) — In discrete geometry, a k set of a finite point set S in the Euclidean plane is a subset of k elements of S that can be strictly separated from the remaining points by a line. More generally, in Euclidean space of higher dimensions, a k set of a… …   Wikipedia

  • Convex polytope — A 3 dimensional convex polytope A convex polytope is a special case of a polytope, having the additional property that it is also a convex set of points in the n dimensional space Rn.[1] Some authors use the terms convex polytope and convex… …   Wikipedia

  • combinatorics — /keuhm buy neuh tawr iks, tor , kom beuh /, n. (used with singular v.) See combinatorial analysis. * * * Branch of mathematics concerned with the selection, arrangement, and combination of objects chosen from a finite set. The number of possible… …   Universalium

  • Locality sensitive hashing — (LSH) is a method of performing probabilistic dimension reduction of high dimensional data. The basic idea is to hash the input items so that similar items are mapped to the same buckets with high probability (the number of buckets being much… …   Wikipedia

  • D-brane — String theory Superstring theory …   Wikipedia

  • List of mathematics articles (M) — NOTOC M M estimator M group M matrix M separation M set M. C. Escher s legacy M. Riesz extension theorem M/M/1 model Maass wave form Mac Lane s planarity criterion Macaulay brackets Macbeath surface MacCormack method Macdonald polynomial Machin… …   Wikipedia

  • Critical dimension — For the minimum feature size in photolithography, see Photolithography. In the renormalization group analysis of phase transitions in physics, a critical dimension is the dimensionality of space at which the character of the phase transition… …   Wikipedia

  • Margin classifier — In machine learning, a margin classifer is a classifier which is able to give an associated distance from the decision boundary for each example. For instance, if a linear classifier (e.g. perceptron or linear discriminant analysis) is used, the… …   Wikipedia

  • Convex optimization — Convex minimization, a subfield of optimization, studies the problem of minimizing convex functions over convex sets. Given a real vector space X together with a convex, real valued function defined on a convex subset of X, the problem is to find …   Wikipedia

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