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Data and information visualization - Wikipedia Visual analytics combines statistical data analysis, data and information visualization, and human analytical reasoning through interactive visual interfaces to help users reach conclusions, gain actionable insights and make informed decisions which are otherwise difficult for computers to do
t-distributed stochastic neighbor embedding - Wikipedia It is based on Stochastic Neighbor Embedding originally developed by Geoffrey Hinton and Sam Roweis, [1] where Laurens van der Maaten and Hinton proposed the t -distributed variant [2] It is a nonlinear dimensionality reduction technique for embedding high-dimensional data for visualization in a low-dimensional space of two or three dimensions
Heat map - Wikipedia Heat map generated from DNA microarray data reflecting gene expression values in several conditions (Eisen et al ) Shaded matrix display from Toussaint Loua (1873) A heat map showing the RF coverage of a drone detection system A heat map (or heatmap) is a 2-dimensional data visualization technique that represents the magnitude of individual values within a dataset as a color The variation in
Orange (software) - Wikipedia Orange is a component-based visual programming software package for data visualization, machine learning, data mining, and data analysis Orange components are called widgets They range from simple data visualization, subset selection, and preprocessing to empirical evaluation of learning algorithms and predictive modeling Visual programming is implemented through an interface in which
Interactive visual analysis - Wikipedia The techniques rely heavily on user interaction and the human visual system, and exist in the intersection between visual analytics and big data It is a branch of data visualization
Exploratory data analysis - Wikipedia In statistics, exploratory data analysis (EDA) or exploratory analytics is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods
Visual analytics - Wikipedia Visual analytics is a multidisciplinary field that includes the following focus areas: [2] Analytical reasoning techniques that enable users to obtain deep insights that directly support assessment, planning, and decision making Data representations and transformations that convert all types of conflicting and dynamic data in ways that support visualization and analysis Techniques to support
Glyph (data visualization) - Wikipedia Four-dimensional data visualization, using VisIt: in three-dimensional phase space a fourth scalar variable is visualized by use of coloured glyphs In the context of data visualization, a glyph is any marker, such as an arrow or similar marking, used to specify part of a visualization This is a representation to visualize data where the data set is presented as a collection of visual objects