enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  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

    Pre-pruning procedures prevent a complete induction of the training set by replacing a stop criterion in the induction algorithm (e.g. max. Tree depth or information gain (Attr)> minGain). Pre-pruning methods are considered to be more efficient because they do not induce an entire set, but rather trees remain small from the start.

  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. Repeated incremental pruning to produce error reduction ...

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

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us

  6. 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 ...

  7. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  8. List of programming languages for artificial intelligence

    en.wikipedia.org/wiki/List_of_programming...

    Jupyter Notebooks can execute cells of Python code, retaining the context between the execution of cells, which usually facilitates interactive data exploration. [5] Elixir is a high-level functional programming language based on the Erlang VM. Its machine-learning ecosystem includes Nx for computing on CPUs and GPUs, Bumblebee and Axon for ...

  9. Delta rule - Wikipedia

    en.wikipedia.org/wiki/Delta_rule

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us; Help; Learn to edit; Community portal; Recent changes; Upload file