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  2. Support vector machine - Wikipedia

    en.wikipedia.org/wiki/Support_vector_machine

    [16] [17] Support vector machine weights have also been used to interpret SVM models in the past. [18] Posthoc interpretation of support vector machine models in order to identify features used by the model to make predictions is a relatively new area of research with special significance in the biological sciences.

  3. 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.

  4. 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.

  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...

    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]

  9. Top five most searched-for recipes in 2024 - AOL

    www.aol.com/top-five-most-searched-recipes...

    A person then dips skewered fruit into the mixture, encasing it in the sugar. Once it dries, it creates a glass-like coating. While tanghulu was popular this year, doctors warned that hot sugar ...