lamp.extratrees
package lamp.extratrees
Type members
Classlikes
case class ClassificationNonLeaf(left: ClassificationTree, right: ClassificationTree, splitFeature: Int, cutpoint: Double, splitMissingIsLess: Boolean) extends ClassificationTree
- Companion:
- object
case class RegressionNonLeaf(left: RegressionTree, right: RegressionTree, splitFeature: Int, cutpoint: Double, splitMissingIsLess: Boolean) extends RegressionTree
- Companion:
- object
Value members
Concrete methods
def buildForestClassification(data: Mat[Double], target: Vec[Int], sampleWeights: Option[Vec[Double]], numClasses: Int, nMin: Int, k: Int, m: Int, parallelism: Int, seed: Long): Seq[ClassificationTree]
Train an extratrees classifier forest
Train an extratrees classifier forest
- Value parameters:
- k
number of features to consider in each split step. The best among these will be chosen.
- m
number of trees
- nMin
minimum sample size for splitting a node
- seed
Returns a list of ClassificationTree objects which can be passed to
predictClassification
def buildForestRegression(data: Mat[Double], target: Vec[Double], nMin: Int, k: Int, m: Int, parallelism: Int, seed: Long): Seq[RegressionTree]
Train an extratrees regression forest
Train an extratrees regression forest
- Value parameters:
- k
number of features to consider in each split step. The best among these will be chosen.
- m
number of trees
- nMin
minimum sample size for splitting a node
- seed
Returns a list of RegressionTree objects which can be passed to
predictRegression