public class DeepLearning extends hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
Modifier and Type | Class and Description |
---|---|
class |
DeepLearning.DeepLearningDriver |
_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 |
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DeepLearning(boolean startup_once) |
DeepLearning(DeepLearningModel.DeepLearningParameters parms)
Main constructor from Deep Learning parameters
|
DeepLearning(DeepLearningModel.DeepLearningParameters parms,
water.Key<DeepLearningModel> key) |
Modifier and Type | Method and Description |
---|---|
hex.ModelCategory[] |
can_build()
Types of models we can build with DeepLearning
|
protected void |
checkMemoryFootPrint_impl() |
void |
cv_computeAndSetOptimalParameters(hex.ModelBuilder[] cvModelBuilders) |
protected int |
desiredChunks(water.fvec.Frame original_fr,
boolean local) |
hex.ToEigenVec |
getToEigenVec() |
boolean |
haveMojo() |
boolean |
havePojo() |
void |
init(boolean expensive)
Initialize the ModelBuilder, validating all arguments and preparing the
training frame.
|
boolean |
isSupervised() |
protected water.fvec.Frame |
rebalance(water.fvec.Frame original_fr,
boolean local,
java.lang.String name) |
protected DeepLearning.DeepLearningDriver |
trainModelImpl() |
algoName, algos, builderVisibility, canLearnFromNAs, checkCustomMetricForEarlyStopping, checkDistributions, checkEarlyStoppingReproducibility, checkMemoryFootPrint, checkResponseVariable, clearInitState, clearValidationErrors, computeCrossValidation, computePriorClassDistribution, cv_buildModels, cv_canBuildMainModelInParallel, cv_initStoppingParameters, cv_mainModelScores, cv_makeAggregateModelMetrics, cv_scoreCVModels, cv_updateOptimalParameters, defaultKey, dest, error_count, error, get, getMessagesByFieldAndSeverity, getName, getSysProperty, 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, nModelsInParallel, numSpecialCols, paramName, raiseReproducibilityWarning, remainingTimeSecs, response, schemaDirectory, separateFeatureVecs, setMaxRuntimeSecsForMainModel, setTrain, setValid, shouldReorder, smallDataSize, stop_requested, timeout, train, trainModel, trainModel, trainModelNested, trainModelNested, trainModelOnH2ONode, valid, validateBinaryResponse, validateStoppingMetric, validationErrors, validationWarnings, vresponse, warn
public DeepLearning(DeepLearningModel.DeepLearningParameters parms)
public DeepLearning(DeepLearningModel.DeepLearningParameters parms, water.Key<DeepLearningModel> key)
public DeepLearning(boolean startup_once)
public hex.ModelCategory[] can_build()
can_build
in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
public boolean havePojo()
havePojo
in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
public boolean haveMojo()
haveMojo
in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
public hex.ToEigenVec getToEigenVec()
getToEigenVec
in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
public boolean isSupervised()
isSupervised
in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
protected DeepLearning.DeepLearningDriver trainModelImpl()
trainModelImpl
in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
public void init(boolean expensive)
init
in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
protected void checkMemoryFootPrint_impl()
checkMemoryFootPrint_impl
in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
public void cv_computeAndSetOptimalParameters(hex.ModelBuilder[] cvModelBuilders)
cv_computeAndSetOptimalParameters
in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
protected water.fvec.Frame rebalance(water.fvec.Frame original_fr, boolean local, java.lang.String name)
rebalance
in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
protected int desiredChunks(water.fvec.Frame original_fr, boolean local)
desiredChunks
in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>