public class XGBoostParametersV3 extends ModelParametersSchemaV3
| Modifier and Type | Field and Description |
|---|---|
TreexgboostXGBoostModelXGBoostParametersBackend |
backend
Backend.
|
TreexgboostXGBoostModelXGBoostParametersBooster |
booster
Booster type
|
double |
colsampleBylevel
(same as col_sample_rate) Column sample rate (from 0.0 to 1.0)
|
double |
colsampleBytree
(same as col_sample_rate_per_tree) Column sample rate per tree (from 0.0 to 1.0)
|
double |
colSampleRate
(same as colsample_bylevel) Column sample rate (from 0.0 to 1.0)
|
double |
colSampleRatePerTree
(same as colsample_bytree) Column sample rate per tree (from 0.0 to 1.0)
|
TreexgboostXGBoostModelXGBoostParametersDMatrixType |
dmatrixType
Type of DMatrix.
|
double |
eta
(same as learn_rate) Learning rate (from 0.0 to 1.0)
|
float |
gamma
(same as min_split_improvement) Minimum relative improvement in squared error reduction for a split to happen
|
int |
gpuId
Which GPU to use.
|
TreexgboostXGBoostModelXGBoostParametersGrowPolicy |
growPolicy
Grow policy - depthwise is standard GBM, lossguide is LightGBM
|
double |
learnRate
(same as eta) Learning rate (from 0.0 to 1.0)
|
float |
maxAbsLeafnodePred
(same as max_delta_step) Maximum absolute value of a leaf node prediction
|
int |
maxBins
For tree_method=hist only: maximum number of bins
|
float |
maxDeltaStep
(same as max_abs_leafnode_pred) Maximum absolute value of a leaf node prediction
|
int |
maxDepth
Maximum tree depth.
|
int |
maxLeaves
For tree_method=hist only: maximum number of leaves
|
double |
minChildWeight
(same as min_rows) Fewest allowed (weighted) observations in a leaf.
|
float |
minDataInLeaf
For tree_method=hist only: the mininum data in a leaf to keep splitting
|
double |
minRows
(same as min_child_weight) Fewest allowed (weighted) observations in a leaf.
|
float |
minSplitImprovement
(same as gamma) Minimum relative improvement in squared error reduction for a split to happen
|
float |
minSumHessianInLeaf
For tree_method=hist only: the mininum sum of hessian in a leaf to keep splitting
|
int |
nEstimators
(same as ntrees) Number of trees.
|
TreexgboostXGBoostModelXGBoostParametersDartNormalizeType |
normalizeType
For booster=dart only: normalize_type
|
int |
ntrees
(same as n_estimators) Number of trees.
|
boolean |
oneDrop
For booster=dart only: one_drop
|
boolean |
quietMode
Enable quiet mode
|
float |
rateDrop
For booster=dart only: rate_drop (0..1)
|
float |
regAlpha
L1 regularization
|
float |
regLambda
L2 regularization
|
double |
sampleRate
(same as subsample) Row sample rate per tree (from 0.0 to 1.0)
|
TreexgboostXGBoostModelXGBoostParametersDartSampleType |
sampleType
For booster=dart only: sample_type
|
int |
scoreTreeInterval
Score the model after every so many trees.
|
long |
seed
Seed for pseudo random number generator (if applicable)
|
float |
skipDrop
For booster=dart only: skip_drop (0..1)
|
double |
subsample
(same as sample_rate) Row sample rate per tree (from 0.0 to 1.0)
|
TreexgboostXGBoostModelXGBoostParametersTreeMethod |
treeMethod
Tree method
|
categoricalEncoding, checkpoint, customMetricFunc, distribution, foldAssignment, foldColumn, huberAlpha, ignoreConstCols, ignoredColumns, keepCrossValidationFoldAssignment, keepCrossValidationPredictions, maxCategoricalLevels, maxRuntimeSecs, modelId, nfolds, offsetColumn, parallelizeCrossValidation, quantileAlpha, responseColumn, scoreEachIteration, stoppingMetric, stoppingRounds, stoppingTolerance, trainingFrame, tweediePower, validationFrame, weightsColumn| Constructor and Description |
|---|
XGBoostParametersV3()
Public constructor
|
| Modifier and Type | Method and Description |
|---|---|
java.lang.String |
toString()
Return the contents of this object as a JSON String.
|
public int ntrees
public int nEstimators
public int maxDepth
public double minRows
public double minChildWeight
public double learnRate
public double eta
public double sampleRate
public double subsample
public double colSampleRate
public double colsampleBylevel
public double colSampleRatePerTree
public double colsampleBytree
public float maxAbsLeafnodePred
public float maxDeltaStep
public int scoreTreeInterval
public long seed
public float minSplitImprovement
public float gamma
public int maxBins
public int maxLeaves
public float minSumHessianInLeaf
public float minDataInLeaf
public TreexgboostXGBoostModelXGBoostParametersTreeMethod treeMethod
public TreexgboostXGBoostModelXGBoostParametersGrowPolicy growPolicy
public TreexgboostXGBoostModelXGBoostParametersBooster booster
public float regLambda
public float regAlpha
public boolean quietMode
public TreexgboostXGBoostModelXGBoostParametersDartSampleType sampleType
public TreexgboostXGBoostModelXGBoostParametersDartNormalizeType normalizeType
public float rateDrop
public boolean oneDrop
public float skipDrop
public TreexgboostXGBoostModelXGBoostParametersDMatrixType dmatrixType
public TreexgboostXGBoostModelXGBoostParametersBackend backend
public int gpuId
public java.lang.String toString()
toString in class ModelParametersSchemaV3