package bags
Type Members
-
class
BaggedModel extends Model[BaggedResult]
Container holding a parallel sequence of models and the sample counts used to train them
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class
BaggedResult extends PredictionResult[Any]
Container with model-wise predictions and logic to compute variances and training row scores
- class BaggedTrainingResult extends TrainingResult
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case class
Bagger(method: Learner, numBags: Int = -1, useJackknife: Boolean = true, biasLearner: Option[Learner] = None) extends Learner with Product with Serializable
A bagger creates an ensemble of models by training the learner on random samples of the training data
A bagger creates an ensemble of models by training the learner on random samples of the training data
Created by maxhutch on 11/14/16.
- method
learner to train each model in the ensemble
- numBags
number of models in the ensemble
-
case class
MultiTaskBagger(method: MultiTaskLearner, numBags: Int = -1, useJackknife: Boolean = true, biasLearner: Option[Learner] = None) extends MultiTaskLearner with Product with Serializable
Create an ensemble of multi-task models
Create an ensemble of multi-task models
- method
learner to train each model in the ensemble
- numBags
number of models in the ensemble