case class Bagger(method: Learner, numBags: Int = -1, useJackknife: Boolean = true, biasLearner: Option[Learner] = None, uncertaintyCalibration: Boolean = true, disableBootstrap: Boolean = false, randBasis: RandBasis = Rand) extends Learner with Product with Serializable
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 base models to aggregate (default of -1 sets the number of models to the number of training rows)
- useJackknife
whether to enable jackknife uncertainty estimate
- biasLearner
learner to use for estimating bias
- uncertaintyCalibration
whether to enable empirical uncertainty calibration
- disableBootstrap
whether to disable bootstrap (useful when
methodimplements its own randomization)- randBasis
breeze RandBasis to use for generating breeze random numbers
- Alphabetic
- By Inheritance
- Bagger
- Product
- Equals
- Learner
- Serializable
- AnyRef
- Any
- Hide All
- Show All
- Public
- Protected
Instance Constructors
- new Bagger(method: Learner, numBags: Int = -1, useJackknife: Boolean = true, biasLearner: Option[Learner] = None, uncertaintyCalibration: Boolean = true, disableBootstrap: Boolean = false, randBasis: RandBasis = Rand)
- method
learner to train each model in the ensemble
- numBags
number of base models to aggregate (default of -1 sets the number of models to the number of training rows)
- useJackknife
whether to enable jackknife uncertainty estimate
- biasLearner
learner to use for estimating bias
- uncertaintyCalibration
whether to enable empirical uncertainty calibration
- disableBootstrap
whether to disable bootstrap (useful when
methodimplements its own randomization)- randBasis
breeze RandBasis to use for generating breeze random numbers
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- val biasLearner: Option[Learner]
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native()
- val disableBootstrap: Boolean
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable])
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native()
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- val method: Learner
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native()
- val numBags: Int
- def productElementNames: Iterator[String]
- Definition Classes
- Product
- val randBasis: RandBasis
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def train(trainingData: Seq[(Vector[Any], Any)], weights: Option[Seq[Double]] = None): BaggedTrainingResult[Any]
Draw with replacement from the training data for each model
- def train(trainingData: Seq[(Vector[Any], Any, Double)]): TrainingResult
Train a model with weights
Train a model with weights
- trainingData
with weights in the form (features, label, weight)
- returns
training result containing a model
- Definition Classes
- Learner
- val uncertaintyCalibration: Boolean
- val useJackknife: Boolean
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()