Deep Learning Function Hinge Loss Training Ppt
This slide explains that hinge loss function is commonly seen in support vector machines. The function has the shape equal to max 0,1-yfx . When yfx less then equal to 0, the loss function is 0, but when yfx more then 0 the error rises exponentially, penalizing misclassified points that are far from the margin disproportionately. As a result, the inaccuracy would grow exponentially to those points.
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Presenting Hinge Loss as a type of Loss Function in Deep Learning. These slides are 100 percent made in PowerPoint and are compatible with all screen types and monitors. They also support Google Slides. Premium Customer Support is available. Suitable for use by managers, employees, and organizations. These slides are easily customizable. You can edit the color, text, icon, and font size to suit your requirements.
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