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  2. Engineering fit - Wikipedia

    en.wikipedia.org/wiki/Engineering_fit

    Engineering fits are generally used as part of geometric dimensioning and tolerancing when a part or assembly is designed. In engineering terms, the "fit" is the clearance between two mating parts, and the size of this clearance determines whether the parts can, at one end of the spectrum, move or rotate independently from each other or, at the other end, are temporarily or permanently joined.

  3. Geared continuous hinge - Wikipedia

    en.wikipedia.org/wiki/Geared_continuous_hinge

    A geared continuous hinge is a type of continuous hinge used mostly on doors in high-traffic entrances and features gear teeth that mesh together under a cap that runs the length of the hinge. The hinges use a number of fasteners to attach the door to the frame from top to bottom to distribute a door’s weight more evenly along the frame to ...

  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. Glossary of mechanical engineering - Wikipedia

    en.wikipedia.org/wiki/Glossary_of_mechanical...

    Backlash – sometimes called lash or play, is a clearance or lost motion in a mechanism caused by gaps between the parts. It can be defined as "the maximum distance or angle through which any part of a mechanical system may be moved in one direction without applying appreciable force or motion to the next part in mechanical sequence", [ 30 ] p ...

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  7. Hinge loss - Wikipedia

    en.wikipedia.org/wiki/Hinge_loss

    The plot shows that the Hinge loss penalizes predictions y < 1, corresponding to the notion of a margin in a support vector machine. In machine learning, the hinge loss is a loss function used for training classifiers. The hinge loss is used for "maximum-margin" classification, most notably for support vector machines (SVMs). [1]