Modifier and Type | Field and Description |
---|---|
float |
alpha |
int |
depth |
int |
ensembleSize |
float |
eta |
float |
gamma |
DataOptions |
general |
float |
lambda |
float |
minWeight |
int |
numThreads |
boolean |
quiet |
XGBoostRegressionTrainer.RegressionType |
rType |
float |
subsample |
float |
subsampleFeatures |
Constructor and Description |
---|
XGBoostOptions() |
public DataOptions general
@Option(longName="regression-metric", usage="Regression type to use. Defaults to LINEAR.") public XGBoostRegressionTrainer.RegressionType rType
@Option(charName=109, longName="ensemble-size", usage="Number of trees in the ensemble.") public int ensembleSize
@Option(charName=97, longName="alpha", usage="L1 regularization term for weights (default 0).") public float alpha
@Option(longName="min-weight", usage="Minimum sum of instance weights needed in a leaf (default 1, range [0,inf]).") public float minWeight
@Option(charName=100, longName="max-depth", usage="Max tree depth (default 6, range (0,inf]).") public int depth
@Option(charName=101, longName="eta", usage="Step size shrinkage parameter (default 0.3, range [0,1]).") public float eta
@Option(longName="subsample-features", usage="Subsample features for each tree (default 1, range (0,1]).") public float subsampleFeatures
@Option(charName=103, longName="gamma", usage="Minimum loss reduction to make a split (default 0, range [0,inf]).") public float gamma
@Option(charName=108, longName="lambda", usage="L2 regularization term for weights (default 1).") public float lambda
@Option(charName=113, longName="quiet", usage="Make the XGBoost training procedure quiet.") public boolean quiet
@Option(longName="subsample", usage="Subsample size for each tree (default 1, range (0,1]).") public float subsample
@Option(charName=116, longName="num-threads", usage="Number of threads to use (default 4, range (1, num hw threads)).") public int numThreads
public String getOptionsDescription()
getOptionsDescription
in interface com.oracle.labs.mlrg.olcut.config.Options
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