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  2. 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]

  3. Cross-validation (statistics) - Wikipedia

    en.wikipedia.org/wiki/Cross-validation_(statistics)

    If an independent sample of validation data is taken from the same population as the training data, it will generally turn out that the model does not fit the validation data as well as it fits the training data. The size of this difference is likely to be large especially when the size of the training data set is small, or when the number of ...

  4. Learning curve (machine learning) - Wikipedia

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

    More abstractly, learning curves plot the difference between learning effort and predictive performance, where "learning effort" usually means the number of training samples, and "predictive performance" means accuracy on testing samples. [3] Learning curves have many useful purposes in ML, including: [4] [5] [6] choosing model parameters ...

  5. Generalization error - Wikipedia

    en.wikipedia.org/wiki/Generalization_error

    Data points were generated from the relationship y = x with white noise added to the y values. In the left column, a set of training points is shown in blue. A seventh order polynomial function was fit to the training data. In the right column, the function is tested on data sampled from the underlying joint probability distribution of x and y ...

  6. Live, virtual, and constructive - Wikipedia

    en.wikipedia.org/wiki/Live,_virtual,_and...

    In this same context, the Virtual Environment would include a doctor practicing CPR on a training mannequin, and the Constructive Environment is the software within the training mannequin that drives its behavior. In a second example, consider fighter pilot training or operational testing. The Live environment is the pilot flying the combat ...

  7. Test data - Wikipedia

    en.wikipedia.org/wiki/Test_data

    Domain testing is a set of techniques focusing on test data. This includes identifying critical inputs, values at the boundaries between equivalence classes, and combinations of inputs that drive the system toward specific outputs. Domain testing helps ensure that various scenarios are effectively tested, including edge cases and unusual ...

  8. Dying To Be Free - The Huffington Post

    projects.huffingtonpost.com/dying-to-be-free...

    The last image we have of Patrick Cagey is of his first moments as a free man. He has just walked out of a 30-day drug treatment center in Georgetown, Kentucky, dressed in gym clothes and carrying a Nike duffel bag.

  9. Overfitting - Wikipedia

    en.wikipedia.org/wiki/Overfitting

    For example, a neural network may be more effective than a linear regression model for some types of data. [14] Increase the amount of training data: If the model is underfitting due to a lack of data, increasing the amount of training data may help. This will allow the model to better capture the underlying patterns in the data. [14]