public class XGBoostModel extends hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput> implements hex.genmodel.algos.tree.SharedTreeGraphConverter, hex.Model.LeafNodeAssignment, hex.Model.Contributions, hex.FeatureInteractionsCollector, hex.Model.UpdateAuxTreeWeights, hex.FriedmanPopescusHCollector
| Modifier and Type | Class and Description |
|---|---|
static class |
XGBoostModel.XGBoostParameters |
hex.Model.AdaptFrameParameters, hex.Model.BigScore, hex.Model.BigScoreChunkPredict, hex.Model.BigScorePredict, hex.Model.Contributions, hex.Model.DeepFeatures, hex.Model.ExemplarMembers, hex.Model.FeatureFrequencies, hex.Model.GetMostImportantFeatures, hex.Model.GetNTrees, hex.Model.GLRMArchetypes, hex.Model.GridSortBy, hex.Model.H2OModelDescriptor, hex.Model.InteractionBuilder, hex.Model.InteractionPair, hex.Model.InteractionSpec, hex.Model.JavaModelStreamWriter, hex.Model.JavaScoringOptions, hex.Model.LeafNodeAssignment, hex.Model.Output, hex.Model.Parameters, hex.Model.PredictScoreResult, hex.Model.RowToTreeAssignment, hex.Model.StagedPredictions, hex.Model.UpdateAuxTreeWeightshex.Model.LeafNodeAssignment.LeafNodeAssignmentType| Constructor and Description |
|---|
XGBoostModel(water.Key<XGBoostModel> selfKey,
XGBoostModel.XGBoostParameters parms,
XGBoostOutput output,
water.fvec.Frame train,
water.fvec.Frame valid) |
| Modifier and Type | Method and Description |
|---|---|
hex.genmodel.algos.tree.SharedTreeGraph |
convert(int treeNumber,
java.lang.String treeClassName) |
hex.genmodel.algos.tree.SharedTreeGraph |
convert(int treeNumber,
java.lang.String treeClass,
hex.genmodel.algos.tree.ConvertTreeOptions options) |
static BoosterParms |
createParams(XGBoostModel.XGBoostParameters p,
int nClasses,
java.lang.String[] coefNames) |
static java.util.Map<java.lang.String,java.lang.Object> |
createParamsMap(XGBoostModel.XGBoostParameters p,
int nClasses,
java.lang.String[] coefNames) |
protected XGBoostModel |
deepClone(water.Key<XGBoostModel> result)
Performs deep clone of given model.
|
static XGBoostModel.XGBoostParameters.Backend |
getActualBackend(XGBoostModel.XGBoostParameters p,
boolean verbose) |
static XGBoostModel.XGBoostParameters.TreeMethod |
getActualTreeMethod(XGBoostModel.XGBoostParameters p) |
hex.FeatureInteractions |
getFeatureInteractions(int maxInteractionDepth,
int maxTreeDepth,
int maxDeepening) |
water.util.TwoDimTable[][] |
getFeatureInteractionsTable(int maxInteractionDepth,
int maxTreeDepth,
int maxDeepening) |
double |
getFriedmanPopescusH(water.fvec.Frame frame,
java.lang.String[] vars) |
XGBoostMojoWriter |
getMojo() |
void |
initActualParamValues() |
void |
initActualParamValuesAfterOutputSetup(boolean isClassifier,
int nclasses) |
boolean |
isFeatureUsedInPredict(java.lang.String featureName) |
hex.ModelMetrics.MetricBuilder |
makeMetricBuilder(java.lang.String[] domain) |
XGBoostModelInfo |
model_info() |
protected water.fvec.Frame |
postProcessPredictions(water.fvec.Frame adaptedFrame,
water.fvec.Frame predictFr,
water.Job j) |
protected water.Keyed |
readAll_impl(water.AutoBuffer ab,
water.Futures fs) |
protected water.Futures |
remove_impl(water.Futures fs,
boolean cascade) |
protected double[] |
score0(double[] data,
double[] preds) |
double[] |
score0(double[] data,
double[] preds,
double offset) |
water.fvec.Frame |
scoreContributions(water.fvec.Frame frame,
water.Key<water.fvec.Frame> destination_key) |
water.fvec.Frame |
scoreContributions(water.fvec.Frame frame,
water.Key<water.fvec.Frame> destination_key,
water.Job<water.fvec.Frame> j,
hex.Model.Contributions.ContributionsOptions options) |
water.fvec.Frame |
scoreLeafNodeAssignment(water.fvec.Frame frame,
hex.Model.LeafNodeAssignment.LeafNodeAssignmentType type,
water.Key<water.fvec.Frame> destination_key) |
XGBoostBigScorePredict |
setupBigScorePredict(boolean isTrain) |
protected XGBoostBigScorePredict |
setupBigScorePredict(hex.Model.BigScore bs) |
XGBoostVariableImportance |
setupVarImp() |
protected boolean |
toJavaCheckTooBig() |
protected water.util.SBPrintStream |
toJavaInit(water.util.SBPrintStream sb,
water.codegen.CodeGeneratorPipeline fileCtx) |
protected void |
toJavaPredictBody(water.util.SBPrintStream sb,
water.codegen.CodeGeneratorPipeline classCtx,
water.codegen.CodeGeneratorPipeline fileCtx,
boolean verboseCode) |
hex.Model.UpdateAuxTreeWeights.UpdateAuxTreeWeightsReport |
updateAuxTreeWeights(water.fvec.Frame frame,
java.lang.String weightsColumn) |
protected water.AutoBuffer |
writeAll_impl(water.AutoBuffer ab) |
adaptFrameForScore, adaptTestForJavaScoring, adaptTestForTrain, adaptTestForTrain, adaptTestForTrain, addMetrics, addModelMetrics, addWarning, auc, AUCPR, checksum_impl, classification_error, compareTo, computeDeviances, containsResponse, data, defaultThreshold, defaultThreshold, deleteCrossValidationFoldAssignment, deleteCrossValidationModels, deleteCrossValidationPreds, deviance, deviance, evaluateAutoModelParameters, exportBinaryModel, exportMojo, fetchAll, fillScoringInfo, getDefaultGridSortBy, getGenModelEncoding, getPojoInterfaces, getToEigenVec, haveMojo, havePojo, importBinaryModel, isDistributionHuber, isFeatureUsedInPredict, isSupervised, last_scored, lift_top_group, likelihood, logloss, loss, mae, makeAdaptFrameParameters, makeBigScoreTask, makeInteraction, makeInteractions, makeInteractions, makePojoWriter, makeSchema, makeScoringDomains, makeScoringNames, makeScoringNames, mean_per_class_error, modelDescriptor, mse, needsPostProcess, predictScoreImpl, r2, resetThreshold, result, rmsle, score, score, score, score, score, score, score, score0, score0, score0PostProcessSupervised, scoreMetrics, scoring_history, scoringDomains, setInputParms, testJavaScoring, testJavaScoring, testJavaScoring, testJavaScoring, testJavaScoring, toJava, toJava, toJava, toJavaAlgo, toJavaModelClassName, toJavaTransform, toJavaUUID, toMojo, toMojo, toString, transform, uploadBinaryModel, writeTodelete_and_lock, delete_and_lock, delete_and_lock, delete, delete, delete, delete, read_lock, read_lock, read_lock, unlock_all, unlock, unlock, unlock, unlock, update, update, update, write_lock_to_read_lock, write_lock, write_lock, write_lockchecksum_impl, checksum, checksum, getKey, readAll, remove_impl, remove_self_key_impl, remove, remove, remove, remove, remove, remove, removeQuietly, writeAllasBytes, clone, copyOver, frozenType, read, readExternal, readJSON, reloadFromBytes, toJsonBytes, toJsonString, write, writeExternal, writeJSONpublic XGBoostModel(water.Key<XGBoostModel> selfKey, XGBoostModel.XGBoostParameters parms, XGBoostOutput output, water.fvec.Frame train, water.fvec.Frame valid)
public XGBoostModelInfo model_info()
public hex.ModelMetrics.MetricBuilder makeMetricBuilder(java.lang.String[] domain)
makeMetricBuilder in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>public void initActualParamValues()
initActualParamValues in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>public static XGBoostModel.XGBoostParameters.TreeMethod getActualTreeMethod(XGBoostModel.XGBoostParameters p)
public void initActualParamValuesAfterOutputSetup(boolean isClassifier,
int nclasses)
public static XGBoostModel.XGBoostParameters.Backend getActualBackend(XGBoostModel.XGBoostParameters p, boolean verbose)
public static java.util.Map<java.lang.String,java.lang.Object> createParamsMap(XGBoostModel.XGBoostParameters p, int nClasses, java.lang.String[] coefNames)
public static BoosterParms createParams(XGBoostModel.XGBoostParameters p, int nClasses, java.lang.String[] coefNames)
protected XGBoostModel deepClone(water.Key<XGBoostModel> result)
protected water.AutoBuffer writeAll_impl(water.AutoBuffer ab)
writeAll_impl in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>protected water.Keyed readAll_impl(water.AutoBuffer ab,
water.Futures fs)
readAll_impl in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>public XGBoostMojoWriter getMojo()
getMojo in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>protected water.fvec.Frame postProcessPredictions(water.fvec.Frame adaptedFrame,
water.fvec.Frame predictFr,
water.Job j)
postProcessPredictions in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>protected double[] score0(double[] data,
double[] preds)
score0 in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>public double[] score0(double[] data,
double[] preds,
double offset)
score0 in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>protected XGBoostBigScorePredict setupBigScorePredict(hex.Model.BigScore bs)
setupBigScorePredict in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>public XGBoostBigScorePredict setupBigScorePredict(boolean isTrain)
public XGBoostVariableImportance setupVarImp()
public water.fvec.Frame scoreContributions(water.fvec.Frame frame,
water.Key<water.fvec.Frame> destination_key)
scoreContributions in interface hex.Model.Contributionspublic water.fvec.Frame scoreContributions(water.fvec.Frame frame,
water.Key<water.fvec.Frame> destination_key,
water.Job<water.fvec.Frame> j,
hex.Model.Contributions.ContributionsOptions options)
scoreContributions in interface hex.Model.Contributionspublic hex.Model.UpdateAuxTreeWeights.UpdateAuxTreeWeightsReport updateAuxTreeWeights(water.fvec.Frame frame,
java.lang.String weightsColumn)
updateAuxTreeWeights in interface hex.Model.UpdateAuxTreeWeightspublic water.fvec.Frame scoreLeafNodeAssignment(water.fvec.Frame frame,
hex.Model.LeafNodeAssignment.LeafNodeAssignmentType type,
water.Key<water.fvec.Frame> destination_key)
scoreLeafNodeAssignment in interface hex.Model.LeafNodeAssignmentprotected water.Futures remove_impl(water.Futures fs,
boolean cascade)
remove_impl in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>public hex.genmodel.algos.tree.SharedTreeGraph convert(int treeNumber,
java.lang.String treeClassName)
convert in interface hex.genmodel.algos.tree.SharedTreeGraphConverterpublic hex.genmodel.algos.tree.SharedTreeGraph convert(int treeNumber,
java.lang.String treeClass,
hex.genmodel.algos.tree.ConvertTreeOptions options)
convert in interface hex.genmodel.algos.tree.SharedTreeGraphConverterpublic boolean isFeatureUsedInPredict(java.lang.String featureName)
isFeatureUsedInPredict in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>protected boolean toJavaCheckTooBig()
toJavaCheckTooBig in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>protected water.util.SBPrintStream toJavaInit(water.util.SBPrintStream sb,
water.codegen.CodeGeneratorPipeline fileCtx)
toJavaInit in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>protected void toJavaPredictBody(water.util.SBPrintStream sb,
water.codegen.CodeGeneratorPipeline classCtx,
water.codegen.CodeGeneratorPipeline fileCtx,
boolean verboseCode)
toJavaPredictBody in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>public hex.FeatureInteractions getFeatureInteractions(int maxInteractionDepth,
int maxTreeDepth,
int maxDeepening)
public water.util.TwoDimTable[][] getFeatureInteractionsTable(int maxInteractionDepth,
int maxTreeDepth,
int maxDeepening)
getFeatureInteractionsTable in interface hex.FeatureInteractionsCollectorpublic double getFriedmanPopescusH(water.fvec.Frame frame,
java.lang.String[] vars)
getFriedmanPopescusH in interface hex.FriedmanPopescusHCollector