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  2. Hyperparameter optimization - Wikipedia

    en.wikipedia.org/wiki/Hyperparameter_optimization

    In machine learning, hyperparameter optimization [1] or tuning is the problem of choosing a set of optimal hyperparameters for a learning algorithm. A hyperparameter is a parameter whose value is used to control the learning process, which must be configured before the process starts. [2] Hyperparameter optimization determines the set of ...

  3. Hyperparameter (machine learning) - Wikipedia

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

    In machine learning, a hyperparameter is a parameter that can be set in order to define any configurable part of a model's learning process. Hyperparameters can be classified as either model hyperparameters (such as the topology and size of a neural network) or algorithm hyperparameters (such as the learning rate and the batch size of an optimizer).

  4. Auto-WEKA - Wikipedia

    en.wikipedia.org/wiki/Auto-WEKA

    Auto-WEKA is an automated machine learning system based on Weka by Chris Thornton, Frank Hutter, Holger H. Hoos and Kevin Leyton-Brown. [1] An extended version was published as Auto-WEKA 2.0. [2] Auto-WEKA was named the first prominent AutoML system in a neutral comparison study. [3] It received the test-of-time award of the SIGKDD conference ...

  5. Model selection - Wikipedia

    en.wikipedia.org/wiki/Model_selection

    Model selection may also refer to the problem of selecting a few representative models from a large set of computational models for the purpose of decision making or optimization under uncertainty. [2] In machine learning, algorithmic approaches to model selection include feature selection, hyperparameter optimization, and statistical learning ...

  6. Parameter space - Wikipedia

    en.wikipedia.org/wiki/Parameter_space

    In machine learning, hyperparameters are used to describe models. In deep learning, ... The study seeks hyperparameter optimization. History

  7. Artificial intelligence engineering - Wikipedia

    en.wikipedia.org/wiki/Artificial_intelligence...

    Engineers evaluate the problem (which could be classification or regression, for example) to determine the most suitable machine learning algorithm, including deep learning paradigms. [7] [8] Once an algorithm is chosen, optimizing it through hyperparameter tuning is essential to enhance efficiency and accuracy. [9]

  8. Jack Nicholson, 87, Seen in Rare Photo While Sharing a ...

    www.aol.com/lifestyle/jack-nicholson-87-seen...

    Jack Nicholson spent some quality time with his loved ones over the holiday season.. In an Instagram post shared by his daughter Lorraine Nicholson on Thursday, Jan. 2, the actor, 87, was captured ...

  9. Hyperparameter - Wikipedia

    en.wikipedia.org/wiki/Hyperparameter

    Hyperparameter may refer to: Hyperparameter (machine learning) Hyperparameter (Bayesian statistics) This page was last edited on 5 ...