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  2. Regularization perspectives on support vector machines

    en.wikipedia.org/wiki/Regularization...

    The training and test-set errors can be measured without bias and in a fair way using accuracy, precision, Auc-Roc, precision-recall, and other metrics. Regularization perspectives on support-vector machines interpret SVM as a special case of Tikhonov regularization, specifically Tikhonov regularization with the hinge loss for a loss function.

  3. Support vector machine - Wikipedia

    en.wikipedia.org/wiki/Support_vector_machine

    The soft-margin support vector machine described above is an example of an empirical risk minimization (ERM) algorithm for the hinge loss. Seen this way, support vector machines belong to a natural class of algorithms for statistical inference, and many of its unique features are due to the behavior of the hinge loss.

  4. Least-squares support vector machine - Wikipedia

    en.wikipedia.org/wiki/Least-squares_support...

    Least-squares support-vector machines (LS-SVM) for statistics and in statistical modeling, are least-squares versions of support-vector machines (SVM), which are a set of related supervised learning methods that analyze data and recognize patterns, and which are used for classification and regression analysis.

  5. Computer-based test interpretation in psychological assessment

    en.wikipedia.org/wiki/Computer-Based_Test...

    The use of CBTIs is found in a variety of psychological domains (e.g., clinical interviewing and problem rating), but is most commonly utilized in personality and neuropsychological assessments. [3] This article will focus on the use of CBTIs in personality assessment, most commonly using the MMPI and its subsequent revised editions.

  6. Structured support vector machine - Wikipedia

    en.wikipedia.org/wiki/Structured_support_vector...

    The structured support-vector machine is a machine learning algorithm that generalizes the Support-Vector Machine (SVM) classifier. Whereas the SVM classifier supports binary classification , multiclass classification and regression , the structured SVM allows training of a classifier for general structured output labels .

  7. New Kindle? Here are 10 accessories you need - AOL

    www.aol.com/lifestyle/new-kindle-here-are-10...

    This page turner works on any capacitive screen (i.e. screens that operate using the body's electrical currents), and includes a clip that goes onto the screen and remote you use can across a ...

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

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

    Finally, the test data set is a data set used to provide an unbiased evaluation of a final model fit on the training data set. [5] If the data in the test data set has never been used in training (for example in cross-validation), the test data set is also called a holdout data set. The term "validation set" is sometimes used instead of "test ...

  9. 15 books we can't wait to read: Most anticipated releases of 2025

    www.aol.com/15-books-cant-wait-read-140018897.html

    The third book in the Yarros’ “Empyrean” series comes out in January from Entangled Publishing. The follow-up to “Fourth Wing” and “Iron Flame” swaps Basgiath War College lessons for ...

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