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kernel of the problem

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  • Kernel methods — (KMs) are a class of algorithms for pattern analysis, whose best known elementis the Support Vector Machine (SVM). The general task of pattern analysis is to find and study general types of relations (for example clusters, rankings, principal… …   Wikipedia

  • Kernel principal component analysis — (kernel PCA) is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with a non linear mapping.ExampleThe two …   Wikipedia

  • The Cantos — by Ezra Pound is a long, incomplete poem in 120 sections, each of which is a canto . Most of it was written between 1915 and 1962, although much of the early work was abandoned and the early cantos, as finally published, date from 1922 onwards.… …   Wikipedia

  • Kernel (computer science) — In computer science, the kernel is the central component of most computer operating systems (OS). Its responsibilities include managing the system s resources (the communication between hardware and software components). As a basic component of… …   Wikipedia

  • Kernel (computing) — A kernel connects the application software to the hardware of a computer In computing, the kernel is the main component of most computer operating systems; it is a bridge between applications and the actual data processing done at the hardware… …   Wikipedia

  • Kernel smoother — A kernel smoother is a statistical technique for estimating a real valued function f(X),,left( Xin mathbb{R}^{p} ight) by using its noisy observations, when no parametric model for this function is known. The estimated function is smooth, and the …   Wikipedia

  • Kernel panic — A kernel panic is an action taken by an operating system upon detecting an internal fatal error from which it cannot safely recover; the term is largely specific to Unix and Unix like systems. The kernel routines that handle panics (in AT T… …   Wikipedia

  • Kernel density estimation — of 100 normally distributed random numbers using different smoothing bandwidths. In statistics, kernel density estimation is a non parametric way of estimating the probability density function of a random variable. Kernel density estimation is a… …   Wikipedia

  • Multivariate kernel density estimation — Kernel density estimation is a nonparametric technique for density estimation i.e., estimation of probability density functions, which is one of the fundamental questions in statistics. It can be viewed as a generalisation of histogram density… …   Wikipedia

  • Kernel trick — In machine learning, the kernel trick is a method for using a linear classifier algorithm to solve a non linear problem by mapping the original non linear observations into a higher dimensional space, where the linear classifier is subsequently… …   Wikipedia

  • Kernel-Regression — Unter Kernel Regression versteht man eine Reihe nichtparametrischer statistischer Methoden, bei denen die Abhängigkeit einer zufälligen Größe von Ausgangsdaten mittels Kerndichteschätzung geschätzt werden. Die Art der Abhängigkeit, dargestellt… …   Deutsch Wikipedia

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