- kernel discriminant analysis
- ядерный дискриминантный анализ
English-Russian electronics dictionary .
kernel discriminant analysis
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Linear discriminant analysis — (LDA) and the related Fisher s linear discriminant are methods used in statistics, pattern recognition and machine learning to find a linear combination of features which characterize or separate two or more classes of objects or events. The… … Wikipedia
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
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
Principal components analysis — Principal component analysis (PCA) is a vector space transform often used to reduce multidimensional data sets to lower dimensions for analysis. Depending on the field of application, it is also named the discrete Karhunen Loève transform (KLT),… … Wikipedia
Principal component analysis — PCA of a multivariate Gaussian distribution centered at (1,3) with a standard deviation of 3 in roughly the (0.878, 0.478) direction and of 1 in the orthogonal direction. The vectors shown are the eigenvectors of the covariance matrix scaled by… … Wikipedia
List of statistics topics — Please add any Wikipedia articles related to statistics that are not already on this list.The Related changes link in the margin of this page (below search) leads to a list of the most recent changes to the articles listed below. To see the most… … Wikipedia
Nonlinear dimensionality reduction — High dimensional data, meaning data that requires more than two or three dimensions to represent, can be difficult to interpret. One approach to simplification is to assume that the data of interest lies on an embedded non linear manifold within… … Wikipedia
Поиск количественных соотношений структура-свойство — Поиск количественных соотношений структура свойство процедура построения моделей, позволяющих по структурам химических соединений предсказывать их разнообразные свойства. За моделями, позволяющими прогнозировать количественные… … Википедия
QSAR — Поиск количественных соотношений структура свойство процедура построения моделей, позволяющих по структурам химических соединений предсказывать их разнообразные свойства. За моделями, позволяющими прогнозировать количественные… … Википедия
Quadratic classifier — A quadratic classifier is used in machine learning to separate measurements of two or more classes of objects or events by a quadric surface. It is a more general version of the linear classifier.The classification problemStatistical… … Wikipedia
