class HingeGradient extends Gradient
Compute gradient and loss for a Hinge loss function, as used in SVM binary classification. See also the documentation for the precise formulation.
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This assumes that the labels are {0,1}
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- new HingeGradient()
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- def compute(data: Vector, label: Double, weights: Vector, cumGradient: Vector): Double
Compute the gradient and loss given the features of a single data point, add the gradient to a provided vector to avoid creating new objects, and return loss.
Compute the gradient and loss given the features of a single data point, add the gradient to a provided vector to avoid creating new objects, and return loss.
- data
features for one data point
- label
label for this data point
- weights
weights/coefficients corresponding to features
- cumGradient
the computed gradient will be added to this vector
- returns
loss
- Definition Classes
- HingeGradient → Gradient
- def compute(data: Vector, label: Double, weights: Vector): (Vector, Double)
Compute the gradient and loss given the features of a single data point.
Compute the gradient and loss given the features of a single data point.
- data
features for one data point
- label
label for this data point
- weights
weights/coefficients corresponding to features
- returns
(gradient: Vector, loss: Double)
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- HingeGradient → Gradient
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