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  2. Hinge loss - Wikipedia

    en.wikipedia.org/wiki/Hinge_loss

    The vertical axis represents the value of the Hinge loss (in blue) and zero-one loss (in green) for fixed t = 1, while the horizontal axis represents the value of the prediction y. The plot shows that the Hinge loss penalizes predictions y < 1, corresponding to the notion of a margin in a support vector machine.

  3. 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 ...

  4. File:Hinge loss vs zero one loss.svg - Wikipedia

    en.wikipedia.org/wiki/File:Hinge_loss_vs_zero...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  5. Multi-vari chart - Wikipedia

    en.wikipedia.org/wiki/Multi-vari_chart

    More recently, the term "multi-vari chart" has been used to describe a visual way to display analysis of variance data (typically be expressed in tabular format). [5] It consists of a series of panels which portray minimum, mean, and maximum responses for each treatment combination of interest rather than for periods of time.

  6. Loss functions for classification - Wikipedia

    en.wikipedia.org/wiki/Loss_functions_for...

    The square loss function is both convex and smooth. However, the square loss function tends to penalize outliers excessively, leading to slower convergence rates (with regards to sample complexity) than for the logistic loss or hinge loss functions. [1]

  7. Bathtub curve - Wikipedia

    en.wikipedia.org/wiki/Bathtub_curve

    The 'bathtub curve' hazard function (blue, upper solid line) is a combination of a decreasing hazard of early failure (red dotted line) and an increasing hazard of wear-out failure (yellow dotted line), plus some constant hazard of random failure (green, lower solid line). The bathtub curve is a particular shape of a failure rate graph.

  8. Influence line - Wikipedia

    en.wikipedia.org/wiki/Influence_line

    An influence line for a given function, such as a reaction, axial force, shear force, or bending moment, is a graph that shows the variation of that function at any given point on a structure due to the application of a unit load at any point on the structure. An influence line for a function differs from a shear, axial, or bending moment diagram.

  9. Vertical line test - Wikipedia

    en.wikipedia.org/wiki/Vertical_line_test

    In mathematics, the vertical line test is a visual way to determine if a curve is a graph of a function or not. A function can only have one output, y , for each unique input, x . If a vertical line intersects a curve on an xy -plane more than once then for one value of x the curve has more than one value of y , and so, the curve does not ...