public class HGLMModel extends hex.Model<HGLMModel,HGLMModel.HGLMParameters,HGLMModel.HGLMModelOutput>
Modifier and Type | Class and Description |
---|---|
static class |
HGLMModel.HGLMModelOutput |
static class |
HGLMModel.HGLMParameters |
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.UpdateAuxTreeWeights
Constructor and Description |
---|
HGLMModel(water.Key<HGLMModel> selfKey,
HGLMModel.HGLMParameters parms,
HGLMModel.HGLMModelOutput output)
the doc = document attached to https://github.com/h2oai/h2o-3/issues/8487, title HGLM_H2O_Implementation.pdf
I will be referring to the doc and different parts of it to explain my implementation.
|
Modifier and Type | Method and Description |
---|---|
hex.ModelMetrics.MetricBuilder |
makeMetricBuilder(java.lang.String[] domain) |
java.lang.String[] |
makeScoringNames() |
protected hex.Model.PredictScoreResult |
predictScoreImpl(water.fvec.Frame fr,
water.fvec.Frame adaptFrm,
java.lang.String destination_key,
water.Job j,
boolean computeMetrics,
water.udf.CFuncRef customMetricFunc) |
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) |
java.lang.String |
toString() |
protected water.AutoBuffer |
writeAll_impl(water.AutoBuffer ab) |
adaptFrameForScore, adaptTestForJavaScoring, adaptTestForTrain, adaptTestForTrain, adaptTestForTrain, addMetrics, addModelMetrics, addWarning, aic, auc, AUCPR, checksum_impl, classification_error, compareTo, computeDeviances, containsResponse, data, defaultThreshold, defaultThreshold, deleteCrossValidationFoldAssignment, deleteCrossValidationModels, deleteCrossValidationPreds, deviance, deviance, evaluateAutoModelParameters, exportBinaryModel, exportMojo, fetchAll, fillScoringInfo, getDefaultGridSortBy, getGenModelEncoding, getMojo, getPojoInterfaces, getToEigenVec, haveMojo, havePojo, importBinaryModel, initActualParamValues, isDistributionHuber, isFeatureUsedInPredict, isFeatureUsedInPredict, isGeneric, isSupervised, last_scored, lift_top_group, likelihood, logloss, loss, mae, makeAdaptFrameParameters, makeBigScoreTask, makeInteraction, makeInteractions, makeInteractions, makePojoWriter, makeSchema, makeScoringDomains, makeScoringNames, mean_per_class_error, modelDescriptor, mse, needsPostProcess, postProcessPredictions, r2, resetThreshold, result, rmsle, score, score, score, score, score, score, score, score, score0, score0, score0, score0PostProcessSupervised, scoreMetrics, scoring_history, scoringDomains, setInputParms, setupBigScorePredict, testJavaScoring, testJavaScoring, testJavaScoring, testJavaScoring, testJavaScoring, toJava, toJava, toJava, toJavaAlgo, toJavaCheckTooBig, toJavaInit, toJavaModelClassName, toJavaPredictBody, toJavaTransform, toJavaUUID, toMojo, toMojo, transform, uploadBinaryModel, writeTo
delete_and_lock, delete_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_lock
checksum_impl, checksum, checksum, getKey, readAll, remove_impl, remove_self_key_impl, remove, remove, remove, remove, remove, remove, removeQuietly, writeAll
public HGLMModel(water.Key<HGLMModel> selfKey, HGLMModel.HGLMParameters parms, HGLMModel.HGLMModelOutput output)
public hex.ModelMetrics.MetricBuilder makeMetricBuilder(java.lang.String[] domain)
makeMetricBuilder
in class hex.Model<HGLMModel,HGLMModel.HGLMParameters,HGLMModel.HGLMModelOutput>
public java.lang.String[] makeScoringNames()
makeScoringNames
in class hex.Model<HGLMModel,HGLMModel.HGLMParameters,HGLMModel.HGLMModelOutput>
protected double[] score0(double[] data, double[] preds)
score0
in class hex.Model<HGLMModel,HGLMModel.HGLMParameters,HGLMModel.HGLMModelOutput>
protected hex.Model.PredictScoreResult predictScoreImpl(water.fvec.Frame fr, water.fvec.Frame adaptFrm, java.lang.String destination_key, water.Job j, boolean computeMetrics, water.udf.CFuncRef customMetricFunc)
predictScoreImpl
in class hex.Model<HGLMModel,HGLMModel.HGLMParameters,HGLMModel.HGLMModelOutput>
protected water.Futures remove_impl(water.Futures fs, boolean cascade)
remove_impl
in class hex.Model<HGLMModel,HGLMModel.HGLMParameters,HGLMModel.HGLMModelOutput>
protected water.AutoBuffer writeAll_impl(water.AutoBuffer ab)
writeAll_impl
in class hex.Model<HGLMModel,HGLMModel.HGLMParameters,HGLMModel.HGLMModelOutput>
protected water.Keyed readAll_impl(water.AutoBuffer ab, water.Futures fs)
readAll_impl
in class hex.Model<HGLMModel,HGLMModel.HGLMParameters,HGLMModel.HGLMModelOutput>
public java.lang.String toString()
toString
in class hex.Model<HGLMModel,HGLMModel.HGLMParameters,HGLMModel.HGLMModelOutput>