case class LinearRegressionLearner(regParam: Option[Double] = None, fitIntercept: Boolean = true) extends Learner with Product with Serializable
Linear and ridge regression learner
Created by maxhutch on 12/6/16.
- fitIntercept
whether to fit an intercept or not
Linear Supertypes
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- new LinearRegressionLearner(regParam: Option[Double] = None, fitIntercept: Boolean = true)
- fitIntercept
whether to fit an intercept or not
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- val fitIntercept: Boolean
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- val regParam: Option[Double]
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- def train(trainingData: Seq[(Vector[Any], Any)], weights: Option[Seq[Double]]): LinearRegressionTrainingResult
Train a linear model via direct inversion.
Train a linear model via direct inversion.
- trainingData
to train on
- weights
for the training rows, if applicable
- returns
a model
- Definition Classes
- LinearRegressionLearner → Learner
- 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
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- Learner
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