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T-distributed stochastic neighbor embedding

Index T-distributed stochastic neighbor embedding

T-distributed Stochastic Neighbor Embedding (t-SNE) is a machine learning algorithm for visualization developed by Laurens van der Maaten and Geoffrey Hinton. [1]

23 relations: Artificial neural network, Bioinformatics, Bisection method, Cancer research, Cauchy distribution, Cluster analysis, Computer security, Curse of dimensionality, Data visualization, Density, ELKI, Euclidean distance, Gaussian function, Geoffrey Hinton, Gradient descent, Intrinsic dimension, Kullback–Leibler divergence, Machine learning, Musical analysis, Nonlinear dimensionality reduction, Perplexity, Probability distribution, Student's t-distribution.

Artificial neural network

Artificial neural networks (ANNs) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains.

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Bioinformatics

Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data.

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Bisection method

The bisection method in mathematics is a root-finding method that repeatedly bisects an interval and then selects a subinterval in which a root must lie for further processing.

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Cancer research

Cancer research is research into cancer to identify causes and develop strategies for prevention, diagnosis, treatment, and cure.

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Cauchy distribution

The Cauchy distribution, named after Augustin Cauchy, is a continuous probability distribution.

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Cluster analysis

Cluster analysis or clustering is the task of grouping a set of objects in such a way that objects in the same group (called a cluster) are more similar (in some sense) to each other than to those in other groups (clusters).

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Computer security

Cybersecurity, computer security or IT security is the protection of computer systems from theft of or damage to their hardware, software or electronic data, as well as from disruption or misdirection of the services they provide.

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Curse of dimensionality

The curse of dimensionality refers to various phenomena that arise when analyzing and organizing data in high-dimensional spaces (often with hundreds or thousands of dimensions) that do not occur in low-dimensional settings such as the three-dimensional physical space of everyday experience.

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Data visualization

Data visualiation or data visualiation is viewed by many disciplines as a modern equivalent of visual communication.

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Density

The density, or more precisely, the volumetric mass density, of a substance is its mass per unit volume.

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ELKI

ELKI (for Environment for DeveLoping KDD-Applications Supported by Index-Structures) is a knowledge discovery in databases (KDD, "data mining") software framework developed for use in research and teaching originally at the database systems research unit of Professor Hans-Peter Kriegel at the Ludwig Maximilian University of Munich, Germany.

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Euclidean distance

In mathematics, the Euclidean distance or Euclidean metric is the "ordinary" straight-line distance between two points in Euclidean space.

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Gaussian function

In mathematics, a Gaussian function, often simply referred to as a Gaussian, is a function of the form: for arbitrary real constants, and.

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Geoffrey Hinton

Geoffrey Everest Hinton One or more of the preceding sentences incorporates text from the royalsociety.org website where: (born 6 December 1947) is a British cognitive psychologist and computer scientist, most noted for his work on artificial neural networks.

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Gradient descent

Gradient descent is a first-order iterative optimization algorithm for finding the minimum of a function.

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Intrinsic dimension

In signal processing of multidimensional signals, for example in computer vision, the intrinsic dimension of the signal describes how many variables are needed to represent the signal.

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Kullback–Leibler divergence

In mathematical statistics, the Kullback–Leibler divergence (also called relative entropy) is a measure of how one probability distribution diverges from a second, expected probability distribution.

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Machine learning

Machine learning is a subset of artificial intelligence in the field of computer science that often uses statistical techniques to give computers the ability to "learn" (i.e., progressively improve performance on a specific task) with data, without being explicitly programmed.

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Musical analysis

Musical analysis is the study of musical structure in either compositions or performances.

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Nonlinear dimensionality reduction

High-dimensional data, meaning data that requires more than two or three dimensions to represent, can be difficult to interpret.

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Perplexity

In information theory, perplexity is a measurement of how well a probability distribution or probability model predicts a sample.

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Probability distribution

In probability theory and statistics, a probability distribution is a mathematical function that provides the probabilities of occurrence of different possible outcomes in an experiment.

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Student's t-distribution

In probability and statistics, Student's t-distribution (or simply the t-distribution) is any member of a family of continuous probability distributions that arises when estimating the mean of a normally distributed population in situations where the sample size is small and population standard deviation is unknown.

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Redirects here:

T-Distributed Stochastic Neighbor Embedding, T-Distributed Stochastic Neighbour Embedding, T-SNE.

References

[1] https://en.wikipedia.org/wiki/T-distributed_stochastic_neighbor_embedding

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