model

Type Members

1. class HingeLoss extends Loss with Serializable

   Implementation of the squared loss function.

2. class L1Regularizer extends Regularizer with Serializable

   The L1Regularizer gradient return the sign as the weight for the regularization.

3. class L2Regularizer extends Regularizer with Serializable

   The L2Regularizer gradient returns the weight as the gradient for the regularization.

4. class LinearModel extends ClassificationModel with Serializable

   A Model trait defines the needed operations on any learning Model.

5. class LogisticLoss extends Loss with Serializable

   Implementation of the logistic loss function.

6. trait Loss extends Serializable

   A Loss trait defines the operation needed to compute the loss function, the prediction function, and the gradient for use in a LinearModel.

7. class PerceptronLoss extends SquaredLoss with Serializable

   Implementation of the perceptron loss function.

8. trait Regularizer extends Serializable

   A regularizer trait defines the gradient operation for computing regularized models.

9. class SquaredLoss extends Loss with Serializable

   Implementation of the squared loss function.

10. class ZeroRegularizer extends Regularizer with Serializable

    The ZeroRegularizer gradient simply returns 0 as the gradient.