HingeLoss

class HingeLoss(margin=1, weight=None, batch_axis=0, **kwargs)

Calculates the hinge loss function often used in SVMs:

(44)\[L = \sum_i max(0, {margin} - {pred}_i \cdot {label}_i)\]

where pred is the classifier prediction and label is the target tensor containing values -1 or 1. label and pred must have the same number of elements.

Parameters:

margin : float

The margin in hinge loss. Defaults to 1.0

weight : float or None

Global scalar weight for loss.

batch_axis : int, default 0

The axis that represents mini-batch.

Inputs:

• pred: prediction tensor with arbitrary shape.
• label: truth tensor with values -1 or 1. Must have the same size as pred.
• sample_weight: element-wise weighting tensor. Must be broadcastable to the same shape as pred. For example, if pred has shape (64, 10) and you want to weigh each sample in the batch separately, sample_weight should have shape (64, 1).

Outputs:

• loss: loss tensor with shape (batch_size,). Dimenions other than batch_axis are averaged out.