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  2. Pruning (artificial neural network) - Wikipedia

    en.wikipedia.org/wiki/Pruning_(artificial_neural...

    Pruning is the practice of removing parameters (which may entail removing individual parameters, or parameters in groups such as by neurons) from an existing artificial neural networks. [1] The goal of this process is to maintain accuracy of the network while increasing its efficiency .

  3. Decision tree pruning - Wikipedia

    en.wikipedia.org/wiki/Decision_tree_pruning

    Pruning is a data compression technique in machine learning and search algorithms that reduces the size of decision trees by removing sections of the tree that are non-critical and redundant to classify instances. Pruning reduces the complexity of the final classifier, and hence improves predictive accuracy by the reduction of overfitting.

  4. Neuroevolution of augmenting topologies - Wikipedia

    en.wikipedia.org/wiki/Neuroevolution_of...

    NeuroEvolution of Augmenting Topologies (NEAT) is a genetic algorithm (GA) for the generation of evolving artificial neural networks (a neuroevolution technique) developed by Kenneth Stanley and Risto Miikkulainen in 2002 while at The University of Texas at Austin. It alters both the weighting parameters and structures of networks, attempting ...

  5. Neural network (machine learning) - Wikipedia

    en.wikipedia.org/wiki/Neural_network_(machine...

    In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains. [1] [2] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain. Artificial ...

  6. Repeated incremental pruning to produce error reduction ...

    en.wikipedia.org/wiki/Repeated_Incremental...

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  7. Neural network - Wikipedia

    en.wikipedia.org/wiki/Neural_network

    There are two main types of neural network. In neuroscience, a biological neural network is a physical structure found in brains and complex nervous systems – a population of nerve cells connected by synapses. In machine learning, an artificial neural network is a mathematical model used to approximate nonlinear functions.

  8. Jacek M. Zurada - Wikipedia

    en.wikipedia.org/wiki/Jacek_M._Zurada

    He has published 450 journal and conference papers, authored or co-authored three books, including the pioneering neural networks text "Introduction to Artificial Neural Systems" (1992), and co-edited a number of volumes in Springer Lecture Notes in Computer Science. His books and articles were cited over 19,000 times (Google Scholar, 2024).

  9. Mathematics of artificial neural networks - Wikipedia

    en.wikipedia.org/wiki/Mathematics_of_artificial...

    An artificial neural network (ANN) combines biological principles with advanced statistics to solve problems in domains such as pattern recognition and game-play. ANNs adopt the basic model of neuron analogues connected to each other in a variety of ways.