public class XGBoostModel extends hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>
| Modifier and Type | Class and Description |
|---|---|
static class |
XGBoostModel.XGBoostParameters |
hex.Model.BigScore, hex.Model.DeepFeatures, hex.Model.ExemplarMembers, hex.Model.GetMostImportantFeatures, hex.Model.GLRMArchetypes, hex.Model.GridSortBy, hex.Model.InteractionBuilder, hex.Model.InteractionPair, hex.Model.InteractionSpec, hex.Model.JavaModelStreamWriter, hex.Model.LeafNodeAssignment, hex.Model.Output, hex.Model.Parameters| 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 |
|---|---|
protected boolean |
bulkBigScorePredict() |
static BoosterParms |
createParams(XGBoostModel.XGBoostParameters p,
int nClasses) |
void |
doScoring(ml.dmlc.xgboost4j.java.Booster booster,
water.fvec.Frame _train,
water.fvec.Frame _trainOrig,
water.fvec.Frame _valid,
water.fvec.Frame _validOrig)
Score an XGBoost model on training and validation data (optional)
Note: every row is scored, all observation weights are assumed to be equal
|
XGBoostMojoWriter |
getMojo() |
hex.ModelMetrics.MetricBuilder |
makeMetricBuilder(java.lang.String[] domain) |
XGBoostModelInfo |
model_info() |
protected water.Keyed |
readAll_impl(water.AutoBuffer ab,
water.Futures fs) |
protected water.Futures |
remove_impl(water.Futures fs) |
water.fvec.Frame |
score(water.fvec.Frame fr,
java.lang.String destination_key,
water.Job j,
boolean computeMetrics) |
double[][] |
score0(water.fvec.Chunk[] chks,
double[] offset,
int[] rowsInChunk,
double[][] tmp,
double[][] preds) |
protected double[] |
score0(double[] data,
double[] preds) |
double[] |
score0(double[] data,
double[] preds,
double offset) |
protected water.AutoBuffer |
writeAll_impl(water.AutoBuffer ab) |
adaptTestForTrain, adaptTestForTrain, addMetrics, addModelMetrics, addWarning, addWarningP, auc, checksum_impl, classification_error, closeBigScorePredict, compareTo, computeDeviances, containsResponse, data, defaultThreshold, defaultThreshold, deleteCrossValidationModels, deleteCrossValidationPreds, deviance, deviance, exportBinaryModel, exportMojo, fetchAll, fillScoringInfo, getDefaultGridSortBy, getPojoInterfaces, getToEigenVec, haveMojo, havePojo, importBinaryModel, isSupervised, last_scored, lift_top_group, logloss, loss, mae, makeBigScoreTask, makeInteraction, makeInteractions, makeInteractions, makeSchema, makeScoringNames, makeScoringNames, mean_per_class_error, mse, needsPostProcess, postProcessPredictions, predictScoreImpl, r2, rmsle, score, score, score, score, score, score, score0, score0, score0PostProcessSupervised, scoreMetrics, scoring_history, scoringDomains, setupBigScorePredict, testJavaScoring, testJavaScoring, testJavaScoring, testJavaScoring, toJava, toJava, toJava, toJavaCheckTooBig, toJavaInit, toJavaNCLASSES, toJavaPredictBody, toJavaPROB, toJavaSuper, toJavaTransform, toMojo, toStringdelete_and_lock, delete_and_lock, delete_and_lock, delete, delete, delete, read_lock, read_lock, read_lock, unlock_all, unlock, unlock, unlock, unlock, update, update, update, write_lock, write_lock, write_lockchecksum, readAll, remove, remove, remove, remove, writeAllpublic 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 static BoosterParms createParams(XGBoostModel.XGBoostParameters p, int nClasses)
protected double[] score0(double[] data,
double[] preds)
score0 in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>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>public void doScoring(ml.dmlc.xgboost4j.java.Booster booster,
water.fvec.Frame _train,
water.fvec.Frame _trainOrig,
water.fvec.Frame _valid,
water.fvec.Frame _validOrig)
throws ml.dmlc.xgboost4j.java.XGBoostError
booster - xgboost model_train - training data in the form of matrix_valid - validation data (optional, can be null)ml.dmlc.xgboost4j.java.XGBoostErrorpublic double[] score0(double[] data,
double[] preds,
double offset)
score0 in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>public double[][] score0(water.fvec.Chunk[] chks,
double[] offset,
int[] rowsInChunk,
double[][] tmp,
double[][] preds)
score0 in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>protected boolean bulkBigScorePredict()
bulkBigScorePredict in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>protected water.Futures remove_impl(water.Futures fs)
remove_impl in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>public water.fvec.Frame score(water.fvec.Frame fr,
java.lang.String destination_key,
water.Job j,
boolean computeMetrics)
throws java.lang.IllegalArgumentException
score in class hex.Model<XGBoostModel,XGBoostModel.XGBoostParameters,XGBoostOutput>java.lang.IllegalArgumentException