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The central principle of D3.js design is to enable the programmer to first use a CSS-style selector to select a given set of Document Object Model (DOM) nodes, then use operators to manipulate them in a similar manner to jQuery. [8]
It is a nonlinear dimensionality reduction technique for embedding high-dimensional data for visualization in a low-dimensional space of two or three dimensions. Specifically, it models each high-dimensional object by a two- or three-dimensional point in such a way that similar objects are modeled by nearby points and dissimilar objects are ...
Jeffrey Michael Heer (born June 15, 1979) is an American computer scientist best known for his work on information visualization and interactive data analysis.He is a professor of computer science & engineering [1] at the University of Washington, where he directs the UW Interactive Data Lab. [2] He co-founded Trifacta with Joe Hellerstein and Sean Kandel in 2012.
Vega acts as a low-level language suited to explanatory figures (the same use case as D3.js), while Vega-Lite is a higher-level language suited to rapidly exploring data. [3] Vega is used in the back end of several data visualization systems, for example Voyager.
Multidimensional scaling (MDS) is a means of visualizing the level of similarity of individual cases of a data set. MDS is used to translate distances between each pair of objects in a set into a configuration of points mapped into an abstract Cartesian space.
Michael Bostock is an American computer scientist and data visualization specialist. He is one of the co-creators of Observable and a key developer of D3.js, [1] a JavaScript library used to produce dynamic, interactive data visualizations for web browsers. [2] He also contributed to the preceding Protovis framework.
A machine learning model is a type of mathematical model that, once "trained" on a given dataset, can be used to make predictions or classifications on new data.
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.