- dimensionality of data
- ОИ, стат. размерность данныхкол-во независимых каналов изображения => размерность пространства спектральных признаков (feature space)
Англо-русский толковый словарь по геоинформатике. В.Ю. Андрианов. 2015.
dimensionality of data
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Data mining — Not to be confused with analytics, information extraction, or data analysis. Data mining (the analysis step of the knowledge discovery in databases process,[1] or KDD), a relatively young and interdisciplinary field of computer science[2][3] is… … 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
Topological data analysis — is a new area of study aimed at having applications in areas such as data mining and computer vision. The main problems are (1) how one infers high dimensionalstructure from low dimensional representations; and (2) how one assembles discrete… … Wikipedia
Curse of dimensionality — The curse of dimensionality refers to various phenomena that arise when analyzing and organizing high dimensional spaces (often with hundreds or thousands of dimensions) that do not occur in low dimensional settings such as the physical space… … Wikipedia
Multifactor dimensionality reduction — (MDR) is a data mining approach for detecting and characterizing combinations of attributes or independent variables that interact to influence a dependent or class variable. MDR was designed specifically to identify interactions among discrete… … Wikipedia
Clustering high-dimensional data — is the cluster analysis of data with anywhere from a few dozen to many thousands of dimensions. Such high dimensional data spaces are often encountered in areas such as medicine, where DNA microarray technology can produce a large number of… … Wikipedia
Determining the number of clusters in a data set — Determining the number of clusters in a data set, a quantity often labeled k as in the k means algorithm, is a frequent problem in data clustering, and is a distinct issue from the process of actually solving the clustering problem. For a certain … Wikipedia
Array data type — Not to be confused with Array data structure. In computer science, an array type is a data type that is meant to describe a collection of elements (values or variables), each selected by one or more indices that can be computed at run time by the … Wikipedia
Auto-encoder — An auto encoder is an artificial neural network used for learning efficient codings.The aim of an auto encoder is to learn a compressed representation (encoding) for a set of data.This means it is being used for dimensionality reduction. More… … Wikipedia
Latent variable — In statistics, latent variables (as opposed to observable variables), are variables that are not directly observed but are rather inferred (through a mathematical model) from other variables that are observed and directly measured. They are also… … Wikipedia
Dimension reduction — For dimensional reduction in physics, see Dimensional reduction. In machine learning, dimension reduction is the process of reducing the number of random variables under consideration, and can be divided into feature selection and feature… … Wikipedia
