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

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

    A test data set is a data set that is independent of the training data set, but that follows the same probability distribution as the training data set. If a model fit to the training data set also fits the test data set well, minimal overfitting has taken place (see figure below). A better fitting of the training data set as opposed to the ...

  3. Medical open network for AI - Wikipedia

    en.wikipedia.org/wiki/Medical_open_network_for_AI

    The distributed data-parallel APIs seamlessly integrate with the native PyTorch distributed module, PyTorch-ignite [21] distributed module, Horovod, XLA, [22] and the SLURM platform. [ 23 ] DL model collection: by offering the MONAI Model Zoo, [ 24 ] MONAI establishes itself as a platform that enables researchers and data scientists to access ...

  4. Kernel method - Wikipedia

    en.wikipedia.org/wiki/Kernel_method

    For many algorithms that solve these tasks, the data in raw representation have to be explicitly transformed into feature vector representations via a user-specified feature map: in contrast, kernel methods require only a user-specified kernel, i.e., a similarity function over all pairs of data points computed using inner products.

  5. Large language model - Wikipedia

    en.wikipedia.org/wiki/Large_language_model

    A large language model (LLM) is a type of machine learning model designed for natural language processing tasks such as language generation.LLMs are language models with many parameters, and are trained with self-supervised learning on a vast amount of text.

  6. Application checkpointing - Wikipedia

    en.wikipedia.org/wiki/Application_checkpointing

    Thus the "checkpoint/restart" capability was born, in which after a number of transactions had been processed, a "snapshot" or "checkpoint" of the state of the application could be taken. If the application failed before the next checkpoint, it could be restarted by giving it the checkpoint information and the last place in the transaction file ...

  7. Model-based testing - Wikipedia

    en.wikipedia.org/wiki/Model-based_testing

    Model-based testing is an application of model-based design for designing and optionally also executing artifacts to perform software testing or system testing. Models can be used to represent the desired behavior of a system under test (SUT), or to represent testing strategies and a test environment.

  8. LoadRunner - Wikipedia

    en.wikipedia.org/wiki/LoadRunner

    LoadRunner is a software testing tool from OpenText.It is used to test applications, measuring system behavior and performance under load.. LoadRunner can simulate millions of users concurrently using application software, recording and later analyzing the performance of key components of the application whilst under load.

  9. SPIN model checker - Wikipedia

    en.wikipedia.org/wiki/SPIN_model_checker

    In addition to model-checking, SPIN can also operate as a simulator, following one possible execution path through the system and presenting the resulting execution trace to the user. Unlike many model-checkers, SPIN does not actually perform model-checking itself, but instead generates C sources for a problem-specific model checker.