public class Infogram extends hex.ModelBuilder<InfogramModel,InfogramModel.InfogramParameters,InfogramModel.InfogramModelOutput>
_coordinator, _desc, _eventPublisher, _fold, _input_parms, _job, _messages, _nclass, _offset, _orig_projection_array, _origDomains, _origNames, _origTrain, _parms, _priorClassDist, _removedCols, _response, _result, _startUpOnceModelBuilder, _train, _treatment, _valid, _vresponse, _weights| Constructor and Description |
|---|
Infogram(boolean startup_once) |
Infogram(InfogramModel.InfogramParameters parms) |
Infogram(InfogramModel.InfogramParameters parms,
water.Key<InfogramModel> key) |
| Modifier and Type | Method and Description |
|---|---|
void |
calculateMeanInfogramInfo(double[][] cmiRaw,
java.util.List<java.util.List<java.lang.String>> columns,
long[] nObs) |
hex.ModelCategory[] |
can_build() |
void |
computeCrossValidation()
This is called before cross-validation is carried out
|
void |
cv_computeAndSetOptimalParameters(hex.ModelBuilder[] cvModelBuilders) |
boolean |
haveMojo() |
boolean |
havePojo() |
void |
init(boolean expensive) |
boolean |
isSupervised() |
protected int |
nModelsInParallel(int folds) |
protected hex.ModelBuilder.Driver |
trainModelImpl() |
algoName, algos, builderVisibility, canLearnFromNAs, checkDistributions, checkEarlyStoppingReproducibility, checkMemoryFootPrint_impl, checkMemoryFootPrint, checkResponseVariable, clearInitState, clearValidationErrors, computePriorClassDistribution, cv_buildModels, cv_canBuildMainModelInParallel, cv_initStoppingParameters, cv_mainModelScores, cv_makeAggregateModelMetrics, cv_scoreCVModels, cv_updateOptimalParameters, defaultKey, desiredChunks, dest, error_count, error, get, getMessagesByFieldAndSeverity, getName, getSysProperty, getToEigenVec, hasFoldCol, hasOffsetCol, hasTreatmentCol, hasWeightCol, hide, ignoreBadColumns, ignoreConstColumns, ignoreInvalidColumns, ignoreStringColumns, ignoreUuidColumns, info, init_adaptFrameToTrain, init_getNClass, initWorkspace, isClassifier, isResponseOptional, isStopped, javaName, logMe, make, make, make, makeCVMetrics, makeCVModelBuilder, makeParameters, makePojoWriter, message, nclasses, nFoldCV, nFoldWork, nModelsInParallel, nModelsInParallel, numSpecialCols, paramName, rebalance, remainingTimeSecs, response, schemaDirectory, separateFeatureVecs, setMaxRuntimeSecsForMainModel, setTrain, setValid, shouldReorder, stop_requested, timeout, train, trainModel, trainModel, trainModelNested, trainModelNested, trainModelOnH2ONode, valid, validateBinaryResponse, validateStoppingMetric, validationErrors, validationWarnings, vresponse, warnpublic Infogram(boolean startup_once)
public Infogram(InfogramModel.InfogramParameters parms)
public Infogram(InfogramModel.InfogramParameters parms, water.Key<InfogramModel> key)
protected hex.ModelBuilder.Driver trainModelImpl()
trainModelImpl in class hex.ModelBuilder<InfogramModel,InfogramModel.InfogramParameters,InfogramModel.InfogramModelOutput>protected int nModelsInParallel(int folds)
nModelsInParallel in class hex.ModelBuilder<InfogramModel,InfogramModel.InfogramParameters,InfogramModel.InfogramModelOutput>public void computeCrossValidation()
computeCrossValidation in class hex.ModelBuilder<InfogramModel,InfogramModel.InfogramParameters,InfogramModel.InfogramModelOutput>public void cv_computeAndSetOptimalParameters(hex.ModelBuilder[] cvModelBuilders)
cv_computeAndSetOptimalParameters in class hex.ModelBuilder<InfogramModel,InfogramModel.InfogramParameters,InfogramModel.InfogramModelOutput>public void calculateMeanInfogramInfo(double[][] cmiRaw,
java.util.List<java.util.List<java.lang.String>> columns,
long[] nObs)
public hex.ModelCategory[] can_build()
can_build in class hex.ModelBuilder<InfogramModel,InfogramModel.InfogramParameters,InfogramModel.InfogramModelOutput>public boolean isSupervised()
isSupervised in class hex.ModelBuilder<InfogramModel,InfogramModel.InfogramParameters,InfogramModel.InfogramModelOutput>public boolean havePojo()
havePojo in class hex.ModelBuilder<InfogramModel,InfogramModel.InfogramParameters,InfogramModel.InfogramModelOutput>public boolean haveMojo()
haveMojo in class hex.ModelBuilder<InfogramModel,InfogramModel.InfogramParameters,InfogramModel.InfogramModelOutput>public void init(boolean expensive)
init in class hex.ModelBuilder<InfogramModel,InfogramModel.InfogramParameters,InfogramModel.InfogramModelOutput>