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  2. Turn-by-turn navigation - Wikipedia

    en.wikipedia.org/wiki/Turn-by-turn_navigation

    Navit turn-by-turn navigation. Turn-by-turn navigation is a feature of some satellite navigation devices where directions for a selected route are continually presented to the user in the form of spoken or visual instructions. [1] The system keeps the user up-to-date about the best route to the destination, and is often updated according to ...

  3. Pursuit–evasion - Wikipedia

    en.wikipedia.org/wiki/Pursuit–evasion

    Pursuit–evasion. Pursuit–evasion (variants of which are referred to as cops and robbers and graph searching) is a family of problems in mathematics and computer science in which one group attempts to track down members of another group in an environment. Early work on problems of this type modeled the environment geometrically. [1]

  4. Stochastic block model - Wikipedia

    en.wikipedia.org/wiki/Stochastic_block_model

    For example, edges may be more common within communities than between communities. Its mathematical formulation was first introduced in 1983 in the field of social network analysis by Paul W. Holland et al. [ 1 ] The stochastic block model is important in statistics , machine learning , and network science , where it serves as a useful ...

  5. Graph neural network - Wikipedia

    en.wikipedia.org/wiki/Graph_neural_network

    t. e. A graph neural network (GNN) belongs to a class of artificial neural networks for processing data that can be represented as graphs. [1][2][3][4][5] Basic building blocks of a graph neural network (GNN). Permutation equivariant layer. Local pooling layer. Global pooling (or readout) layer. Colors indicate features.

  6. Bayesian network - Wikipedia

    en.wikipedia.org/wiki/Bayesian_network

    Automatically learning the graph structure of a Bayesian network (BN) is a challenge pursued within machine learning. The basic idea goes back to a recovery algorithm developed by Rebane and Pearl [ 7 ] and rests on the distinction between the three possible patterns allowed in a 3-node DAG:

  7. Topological data analysis - Wikipedia

    en.wikipedia.org/wiki/Topological_data_analysis

    Topological data analysis. In applied mathematics, topological data analysis (TDA) is an approach to the analysis of datasets using techniques from topology. Extraction of information from datasets that are high-dimensional, incomplete and noisy is generally challenging. TDA provides a general framework to analyze such data in a manner that is ...

  8. Flow network - Wikipedia

    en.wikipedia.org/wiki/Flow_network

    Flow network. In graph theory, a flow network (also known as a transportation network) is a directed graph where each edge has a capacity and each edge receives a flow. The amount of flow on an edge cannot exceed the capacity of the edge. Often in operations research, a directed graph is called a network, the vertices are called nodes and the ...

  9. Predictive analytics - Wikipedia

    en.wikipedia.org/wiki/Predictive_analytics

    Predictive analytics is a form of business analytics applying machine learning to generate a predictive model for certain business applications. As such, it encompasses a variety of statistical techniques from predictive modeling and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. [1]

  1. Related searches turn by turn graph theory in machine learning examples in healthcare providers

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