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Learn the topological structure of the input data by building a corresponding graph approximation. More information about the Growing Neural Gas algorithm can be found in B. Fritzke, A Growing Neural Gas Network Learns Topologies, in G. Tesauro, D. S. Touretzky, and T. K. Leen (editors), Advances in Neural Information Processing Systems 7, pages 625-632. MIT Press, Cambridge MA, 1995. A java implementation is available at: http://www.neuroinformatik.ruhr-uni-bochum.de/ini/VDM/research/gsn/DemoGNG/GNG.html Attributes and methods of interest: graph -- The corresponding Graph object
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__metaclass__ This Metaclass is meant to overwrite doc strings of methods like execute, stop_training, inverse with the ones defined in the corresponding private methods _execute, _stop_training, _inverse, etc... |
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_train_seq List of tuples: [(training-phase1, stop-training-phase1), (training-phase2, stop_training-phase2), ... |
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dtype dtype |
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input_dim Input dimensions |
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output_dim Output dimensions |
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supported_dtypes Supported dtypes |
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Growing Neural Gas algorithm. Input arguments: start_pos -- sequence of two arrays containing the position of the first two nodes in the GNG graph. In unspecified, the initial nodes are chosen with a random position generated from a gaussian distribution with zero mean and unit variance. eps_b -- coefficient of movement of the nearest node to a new data point. Typical values are 0 < eps_b << 1 . Default: 0.2 eps_n -- coefficient of movement of the neighbours of the nearest node to a new data point. Typical values are 0 < eps_n << eps_b . Default: 0.006 max_age -- remove an edge after 'max_age' updates. Typical values are 10 < max_age < lambda . Default: 50 lambda_ -- insert a new node after 'lambda_' steps. Typical values are O(100). Default: 100 alpha -- when a new node is inserted, multiply the error of the nodes from which it generated by 0<alpha<1. A typical value is 0.5. Default: 0.5 d -- each step the error of the nodes are multiplied by 0<d<1. Typical values are close to 1. Default: 0.995 max_nodes -- maximal number of nodes in the graph. Default: 2^31 - 1
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Return the two nodes in the graph that are nearest to x and their squared distances. (Return ([node1, node2], [dist1, dist2]) |
Return the list of dtypes supported by this node.
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Insert a new node in the graph where it is more necessary (i.e. where the error is the largest). |
Move a node by eps in the direction x. |
Remove all edges older than the maximal age. |
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Assign each point in the input data to the nearest node in the graph. Return the list of the nearest node instances, and the list of distances. Executing this function will close the training phase if necessary. |
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