optim

Type Members

1. abstract class AbstractOptimizer extends AnyRef

2. class AccuracyResult extends ValidationResult

   Represent an accuracy result.

3. class Adadelta[T] extends OptimMethod[T]

   Adadelta implementation for SGD: http://arxiv.

4. class Adagrad[T] extends OptimMethod[T]

   An implementation of Adagrad.

5. class Adam[T] extends OptimMethod[T]

   An implementation of Adam http://arxiv.

6. class Adamax[T] extends OptimMethod[T]

   An implementation of Adamax http://arxiv.

7. class ContiguousResult extends ValidationResult

   A generic result type who's data is contiguous float.

8. class DistriOptimizer[T] extends Optimizer[T, MiniBatch[T]]

   The optimizer run on a distributed cluster.

9. class DistriOptimizerV2[T] extends Optimizer[T, MiniBatch[T]]

   The optimizer run on a distributed cluster.

10. class DistriValidator[T] extends Validator[T, MiniBatch[T]]

    Validate model on a distributed cluster.

11. class Evaluator[T] extends Serializable

    model evaluator

12. class Ftrl[T] extends OptimMethod[T]

    An implementation of Ftrl https://www.

13. class HitRatio[T] extends ValidationMethod[T]

    Hit Ratio(HR).

14. class L1L2Regularizer[T] extends Regularizer[T]

    Apply both L1 and L2 regularization

15. case class L1Regularizer[T](l1: Double)(implicit evidence$3: ClassTag[T], ev: TensorNumeric[T]) extends L1L2Regularizer[T] with Product with Serializable

    Apply L1 regularization

16. case class L2Regularizer[T](l2: Double)(implicit evidence$4: ClassTag[T], ev: TensorNumeric[T]) extends L1L2Regularizer[T] with Product with Serializable

    Apply L2 regularization

17. class LBFGS[T] extends OptimMethod[T]

    This implementation of L-BFGS relies on a user-provided line search function (state.

18. class LarsSGD[T] extends SGD[T]

    An implementation of LARS https://arxiv.

19. trait LineSearch[T] extends AnyRef

    Line Search strategy

20. class LocalOptimizer[T] extends Optimizer[T, MiniBatch[T]]

    Optimize a model on a single machine

21. class LocalPredictor[T] extends Serializable

    Predictor for local data

22. class LocalValidator[T] extends Validator[T, MiniBatch[T]]

    Validate a model on a single machine Use given dataset with certain validation methods such as Top1Accuracy as an argument of its test method

23. class Loss[T] extends ValidationMethod[T]

    This evaluation method is calculate loss of output with respect to target

24. class LossResult extends ContiguousResult

    Use loss as a validation result

25. case class LossWithElapsedTime(index: Int, loss: Double, elapsed: Long) extends Product with Serializable

26. class MAE[T] extends ValidationMethod[T]

    This evaluation method is calculate mean absolute error of output with respect to target

27. class MAPMultiIOUValidationResult extends ValidationResult

28. class MAPType extends Serializable

29. class MAPValidationResult extends ValidationResult

    The MAP Validation Result.

30. class MeanAveragePrecision[T] extends ValidationMethod[T]

    Calculate the Mean Average Precision (MAP).

31. class MeanAveragePrecisionObjectDetection[T] extends ValidationMethod[T]

    MeanAveragePrecision for Object Detection The class label begins with 0

32. class Metrics extends Serializable

    Performance metrics for the training process.

33. class NDCG[T] extends ValidationMethod[T]

    Normalized Discounted Cumulative Gain(NDCG).

34. trait OptimMethod[T] extends Serializable

    Similar to torch Optim method, which is used to update the parameter

35. abstract class Optimizer[T, D] extends AnyRef

    Optimizer is an abstract class which is used to train a model automatically with some certain optimization algorithms.

36. trait OptimizerLogger extends AnyRef

37. class PRAUCResult extends ValidationResult

38. class ParallelAdam[T] extends OptimMethod[T]

    An multi-thread implementation of Adam http://arxiv.

39. class ParallelOptimizer[T] extends Optimizer[T, MiniBatch[T]]

    The optimizer run on a distributed cluster.

40. case class ParamSegments[T](start: Int, length: Int, method: OptimMethod[T]) extends Product with Serializable

41. class PrecisionRecallAUC[T] extends ValidationMethod[T]

    Precision Recall Area Under Curve will compute the precision-recall pairs and get the area under the curve.

42. class PredictionService[T] extends AnyRef

    In this service, concurrency is kept not greater than numThreads by a BlockingQueue, which contains available model instances.

43. class Predictor[T] extends Serializable

    Predictor for distributed data

44. class RMSprop[T] extends OptimMethod[T]

    An implementation of RMSprop

45. trait Regularizer[T] extends Serializable

    It is a trait for all regularizers.

46. class SGD[T] extends OptimMethod[T]

    A plain implementation of SGD

47. class Top1Accuracy[T] extends ValidationMethod[T]

    Caculate the percentage that output's max probability index equals target

48. class Top5Accuracy[T] extends ValidationMethod[T]

    Calculate the percentage that target in output's top5 probability indexes

49. class TrainingContext[T] extends Serializable

50. class TreeNNAccuracy[T] extends ValidationMethod[T]

    This is a metric to measure the accuracy of Tree Neural Network/Recursive Neural Network

51. trait Trigger extends Serializable

    A trigger specifies a timespot or several timespots during training, and a corresponding action will be taken when the timespot(s) is reached.

52. trait ValidationMethod[T] extends Serializable

    A method defined to evaluate the model.

53. trait ValidationResult extends Serializable

    A result that calculate the numeric value of a validation method.

54. abstract class Validator[T, D] extends AnyRef

    Validator is an abstract class which is used to test a model automatically with some certain validation methods such as Top1Accuracy, as an argument of its test method.