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  2. Support vector machine - Wikipedia

    en.wikipedia.org/wiki/Support_vector_machine

    Potential drawbacks of the SVM include the following aspects: Requires full labeling of input data; Uncalibrated class membership probabilities—SVM stems from Vapnik's theory which avoids estimating probabilities on finite data; The SVM is only directly applicable for two-class tasks.

  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. 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.

  5. Kernel method - Wikipedia

    en.wikipedia.org/wiki/Kernel_method

    Empirically, for machine learning heuristics, choices of a function that do not satisfy Mercer's condition may still perform reasonably if at least approximates the intuitive idea of similarity. [6] Regardless of whether k {\displaystyle k} is a Mercer kernel, k {\displaystyle k} may still be referred to as a "kernel".

  6. Hinge loss - Wikipedia

    en.wikipedia.org/wiki/Hinge_loss

    The hinge loss is a convex function, so many of the usual convex optimizers used in machine learning can work with it. It is not differentiable , but has a subgradient with respect to model parameters w of a linear SVM with score function y = w ⋅ x {\displaystyle y=\mathbf {w} \cdot \mathbf {x} } that is given by

  7. Australia to charge tech companies for news content if they ...

    www.aol.com/news/australia-charge-tech-companies...

    SYDNEY (Reuters) -Australia's centre-left government said on Thursday it planned new rules that would charge big tech firms millions of dollars if they did not pay Australian media companies for ...

  8. Regularization perspectives on support vector machines

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

    SVM algorithms categorize binary data, with the goal of fitting the training set data in a way that minimizes the average of the hinge-loss function and L2 norm of the learned weights. This strategy avoids overfitting via Tikhonov regularization and in the L2 norm sense and also corresponds to minimizing the bias and variance of our estimator ...

  9. When will Marquise 'Hollywood' Brown return? Latest injury ...

    www.aol.com/marquise-hollywood-brown-return...

    The Chiefs host the Los Angeles Chargers (8-4) in a massive AFC West clash on "Sunday Night Football," and with a win can claim the AFC West crown for the ninth consecutive season.. This ...