public class BoostingStrategy
extends java.lang.Object
implements scala.Serializable, scala.Product
GradientBoostedTrees
.
param: treeStrategy Parameters for the tree algorithm. We support regression and binary
classification for boosting. Impurity setting will be ignored.
param: loss Loss function used for minimization during gradient boosting.
param: numIterations Number of iterations of boosting. In other words, the number of
weak hypotheses used in the final model.
param: learningRate Learning rate for shrinking the contribution of each estimator. The
learning rate should be between in the interval (0, 1]
param: validationTol validationTol is a condition which decides iteration termination when
runWithValidation is used.
The end of iteration is decided based on below logic:
If the current loss on the validation set is > 0.01, the diff
of validation error is compared to relative tolerance which is
validationTol * (current loss on the validation set).
If the current loss on the validation set is <= 0.01, the diff
of validation error is compared to absolute tolerance which is
validationTol * 0.01.
Ignored when
org.apache.spark.mllib.tree.GradientBoostedTrees.run()
is used.
Constructor and Description |
---|
BoostingStrategy(Strategy treeStrategy,
Loss loss,
int numIterations,
double learningRate,
double validationTol) |
Modifier and Type | Method and Description |
---|---|
static BoostingStrategy |
defaultParams(scala.Enumeration.Value algo) |
static BoostingStrategy |
defaultParams(java.lang.String algo) |
double |
getLearningRate() |
Loss |
getLoss() |
int |
getNumIterations() |
Strategy |
getTreeStrategy() |
double |
getValidationTol() |
double |
learningRate() |
Loss |
loss() |
int |
numIterations() |
void |
setLearningRate(double x$1) |
void |
setLoss(Loss x$1) |
void |
setNumIterations(int x$1) |
void |
setTreeStrategy(Strategy x$1) |
void |
setValidationTol(double x$1) |
Strategy |
treeStrategy() |
double |
validationTol() |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
public static BoostingStrategy defaultParams(java.lang.String algo)
public static BoostingStrategy defaultParams(scala.Enumeration.Value algo)
public Strategy treeStrategy()
public void setTreeStrategy(Strategy x$1)
public Loss loss()
public void setLoss(Loss x$1)
public int numIterations()
public void setNumIterations(int x$1)
public double learningRate()
public void setLearningRate(double x$1)
public double validationTol()
public void setValidationTol(double x$1)
public Strategy getTreeStrategy()
public Loss getLoss()
public int getNumIterations()
public double getLearningRate()
public double getValidationTol()